{
 "cells": [
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   "source": [
    "<div align=\"right\" style=\"text-align: right\"><i>Peter Norvig, Oct 2017<br>Data update: March 2025</i></div>\n",
    "\n",
    "# Bicycling Statistics\n",
    "\n",
    "Bicycling is a great way to get some exercise, enjoy the outside, and go places. This notebook tracks [my cycling performance](https://www.strava.com/athletes/575579) against various goals:\n",
    "- **Distance**: I do about 6,000 miles a year.\n",
    "- **Climbing**: In 2022, I climbed to *space* (100 km of total elevation gain).\n",
    "- **Explorer Tiles**: In 2022, I started tracking the 1-mile-square [explorer tiles](https://rideeverytile.com/) I have visited.\n",
    "- **Wandering**: In 2020, I started using [Wandrer.earth](https://wandrer.earth/athletes/3534/) to track what new roads I have ridden.\n",
    "- **Eddington Number**: I've done 69 miles or more on 69 different days. So 69 is my Eddington Number.\n",
    "- **Speed**: I'm not going particularly fast, but I am interested in understanding how my speed varies with the steepness of the hill.\n",
    "\n",
    "This notebook is mostly for my own benefit, but if you're a cyclist you're welcome to adapt it to your own data, and if you're a data scientist, you might find it an interesting example of exploratory data analysis.  The companion notebook [**BikeCode.ipynb**](BikeCode.ipynb) has the implementation details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%run BikeCode.ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Yearly Totals\n",
    "\n",
    "Here are my overall stats for each year since I started keeping track in mid-2014. I have done 6,000 miles per year since 2016, except for 2020 when an injury kept me sidelined for two months (also, Covid). The columns keep track of the total **hours** on the bike, distance traveled in **miles**, and total **feet** climbed. Then there are some columns that are derived from these: **mph** is **miles / hour**; **vam** is vertical meters ascended per hour (or **feet × 0.3048 / hours**); **fpmi** is **feet / miles**; **pct** is the grade in percent (or **feet × 100 / miles / 5280**), and finally **kms** and **meters** are the metric equivalents of **miles** and **feet**.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>rides</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2024</td>\n",
       "      <td>511.68</td>\n",
       "      <td>6344</td>\n",
       "      <td>264838</td>\n",
       "      <td>393</td>\n",
       "      <td>12.40</td>\n",
       "      <td>158.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.79</td>\n",
       "      <td>10207.50</td>\n",
       "      <td>80723.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2023</td>\n",
       "      <td>541.68</td>\n",
       "      <td>6316</td>\n",
       "      <td>243100</td>\n",
       "      <td>372</td>\n",
       "      <td>11.66</td>\n",
       "      <td>137.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.73</td>\n",
       "      <td>10162.44</td>\n",
       "      <td>74097.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2022</td>\n",
       "      <td>532.93</td>\n",
       "      <td>6028</td>\n",
       "      <td>362323</td>\n",
       "      <td>349</td>\n",
       "      <td>11.31</td>\n",
       "      <td>207.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1.14</td>\n",
       "      <td>9699.05</td>\n",
       "      <td>110436.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2021</td>\n",
       "      <td>490.53</td>\n",
       "      <td>6064</td>\n",
       "      <td>196634</td>\n",
       "      <td>319</td>\n",
       "      <td>12.36</td>\n",
       "      <td>122.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.61</td>\n",
       "      <td>9756.98</td>\n",
       "      <td>59934.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2020</td>\n",
       "      <td>438.88</td>\n",
       "      <td>5341</td>\n",
       "      <td>94777</td>\n",
       "      <td>266</td>\n",
       "      <td>12.17</td>\n",
       "      <td>66.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.34</td>\n",
       "      <td>8593.67</td>\n",
       "      <td>28888.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2019</td>\n",
       "      <td>476.32</td>\n",
       "      <td>6016</td>\n",
       "      <td>149797</td>\n",
       "      <td>438</td>\n",
       "      <td>12.63</td>\n",
       "      <td>96.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.47</td>\n",
       "      <td>9679.74</td>\n",
       "      <td>45658.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2018</td>\n",
       "      <td>475.93</td>\n",
       "      <td>6101</td>\n",
       "      <td>158642</td>\n",
       "      <td>440</td>\n",
       "      <td>12.82</td>\n",
       "      <td>102.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9816.51</td>\n",
       "      <td>48354.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2017</td>\n",
       "      <td>567.33</td>\n",
       "      <td>7356</td>\n",
       "      <td>202096</td>\n",
       "      <td>367</td>\n",
       "      <td>12.97</td>\n",
       "      <td>109.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.52</td>\n",
       "      <td>11835.80</td>\n",
       "      <td>61599.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2016</td>\n",
       "      <td>486.38</td>\n",
       "      <td>6339</td>\n",
       "      <td>201453</td>\n",
       "      <td>327</td>\n",
       "      <td>13.03</td>\n",
       "      <td>126.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>10199.45</td>\n",
       "      <td>61403.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2015</td>\n",
       "      <td>419.95</td>\n",
       "      <td>5452</td>\n",
       "      <td>209859</td>\n",
       "      <td>244</td>\n",
       "      <td>12.98</td>\n",
       "      <td>152.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.73</td>\n",
       "      <td>8772.27</td>\n",
       "      <td>63965.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2014</td>\n",
       "      <td>191.03</td>\n",
       "      <td>2469</td>\n",
       "      <td>118481</td>\n",
       "      <td>100</td>\n",
       "      <td>12.92</td>\n",
       "      <td>189.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>3972.62</td>\n",
       "      <td>36113.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  year   hours  miles    feet  rides    mph    vam  fpmi   pct       kms  \\\n",
       "  2024  511.68   6344  264838    393  12.40  158.0  42.0  0.79  10207.50   \n",
       "  2023  541.68   6316  243100    372  11.66  137.0  38.0  0.73  10162.44   \n",
       "  2022  532.93   6028  362323    349  11.31  207.0  60.0  1.14   9699.05   \n",
       "  2021  490.53   6064  196634    319  12.36  122.0  32.0  0.61   9756.98   \n",
       "  2020  438.88   5341   94777    266  12.17   66.0  18.0  0.34   8593.67   \n",
       "  2019  476.32   6016  149797    438  12.63   96.0  25.0  0.47   9679.74   \n",
       "  2018  475.93   6101  158642    440  12.82  102.0  26.0  0.49   9816.51   \n",
       "  2017  567.33   7356  202096    367  12.97  109.0  27.0  0.52  11835.80   \n",
       "  2016  486.38   6339  201453    327  13.03  126.0  32.0  0.60  10199.45   \n",
       "  2015  419.95   5452  209859    244  12.98  152.0  38.0  0.73   8772.27   \n",
       "  2014  191.03   2469  118481    100  12.92  189.0  48.0  0.91   3972.62   \n",
       "\n",
       "    meters  \n",
       "   80723.0  \n",
       "   74097.0  \n",
       "  110436.0  \n",
       "   59934.0  \n",
       "   28888.0  \n",
       "   45658.0  \n",
       "   48354.0  \n",
       "   61599.0  \n",
       "   61403.0  \n",
       "   63965.0  \n",
       "   36113.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yearly"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And here's the same data on a per day (or per ride) basis, assuming I ride 6 days a week, 50 weeks a year:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>rides</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2024</td>\n",
       "      <td>1.7</td>\n",
       "      <td>21.1</td>\n",
       "      <td>882.8</td>\n",
       "      <td>393</td>\n",
       "      <td>12.40</td>\n",
       "      <td>158.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.79</td>\n",
       "      <td>34.0</td>\n",
       "      <td>269.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2023</td>\n",
       "      <td>1.8</td>\n",
       "      <td>21.1</td>\n",
       "      <td>810.3</td>\n",
       "      <td>372</td>\n",
       "      <td>11.66</td>\n",
       "      <td>137.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.73</td>\n",
       "      <td>33.9</td>\n",
       "      <td>247.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2022</td>\n",
       "      <td>1.8</td>\n",
       "      <td>20.1</td>\n",
       "      <td>1207.7</td>\n",
       "      <td>349</td>\n",
       "      <td>11.31</td>\n",
       "      <td>207.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1.14</td>\n",
       "      <td>32.3</td>\n",
       "      <td>368.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2021</td>\n",
       "      <td>1.6</td>\n",
       "      <td>20.2</td>\n",
       "      <td>655.4</td>\n",
       "      <td>319</td>\n",
       "      <td>12.36</td>\n",
       "      <td>122.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.61</td>\n",
       "      <td>32.5</td>\n",
       "      <td>199.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2020</td>\n",
       "      <td>1.5</td>\n",
       "      <td>17.8</td>\n",
       "      <td>315.9</td>\n",
       "      <td>266</td>\n",
       "      <td>12.17</td>\n",
       "      <td>66.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.34</td>\n",
       "      <td>28.6</td>\n",
       "      <td>96.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2019</td>\n",
       "      <td>1.6</td>\n",
       "      <td>20.1</td>\n",
       "      <td>499.3</td>\n",
       "      <td>438</td>\n",
       "      <td>12.63</td>\n",
       "      <td>96.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.47</td>\n",
       "      <td>32.3</td>\n",
       "      <td>152.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2018</td>\n",
       "      <td>1.6</td>\n",
       "      <td>20.3</td>\n",
       "      <td>528.8</td>\n",
       "      <td>440</td>\n",
       "      <td>12.82</td>\n",
       "      <td>102.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>32.7</td>\n",
       "      <td>161.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2017</td>\n",
       "      <td>1.9</td>\n",
       "      <td>24.5</td>\n",
       "      <td>673.7</td>\n",
       "      <td>367</td>\n",
       "      <td>12.97</td>\n",
       "      <td>109.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.52</td>\n",
       "      <td>39.5</td>\n",
       "      <td>205.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2016</td>\n",
       "      <td>1.6</td>\n",
       "      <td>21.1</td>\n",
       "      <td>671.5</td>\n",
       "      <td>327</td>\n",
       "      <td>13.03</td>\n",
       "      <td>126.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>34.0</td>\n",
       "      <td>204.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2015</td>\n",
       "      <td>1.4</td>\n",
       "      <td>18.2</td>\n",
       "      <td>699.5</td>\n",
       "      <td>244</td>\n",
       "      <td>12.98</td>\n",
       "      <td>152.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.73</td>\n",
       "      <td>29.2</td>\n",
       "      <td>213.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2014</td>\n",
       "      <td>0.6</td>\n",
       "      <td>8.2</td>\n",
       "      <td>394.9</td>\n",
       "      <td>100</td>\n",
       "      <td>12.92</td>\n",
       "      <td>189.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>13.2</td>\n",
       "      <td>120.4</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "  year  hours  miles    feet  rides    mph    vam  fpmi   pct   kms  meters\n",
       "  2024    1.7   21.1   882.8    393  12.40  158.0  42.0  0.79  34.0   269.1\n",
       "  2023    1.8   21.1   810.3    372  11.66  137.0  38.0  0.73  33.9   247.0\n",
       "  2022    1.8   20.1  1207.7    349  11.31  207.0  60.0  1.14  32.3   368.1\n",
       "  2021    1.6   20.2   655.4    319  12.36  122.0  32.0  0.61  32.5   199.8\n",
       "  2020    1.5   17.8   315.9    266  12.17   66.0  18.0  0.34  28.6    96.3\n",
       "  2019    1.6   20.1   499.3    438  12.63   96.0  25.0  0.47  32.3   152.2\n",
       "  2018    1.6   20.3   528.8    440  12.82  102.0  26.0  0.49  32.7   161.2\n",
       "  2017    1.9   24.5   673.7    367  12.97  109.0  27.0  0.52  39.5   205.3\n",
       "  2016    1.6   21.1   671.5    327  13.03  126.0  32.0  0.60  34.0   204.7\n",
       "  2015    1.4   18.2   699.5    244  12.98  152.0  38.0  0.73  29.2   213.2\n",
       "  2014    0.6    8.2   394.9    100  12.92  189.0  48.0  0.91  13.2   120.4"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Climbing \n",
    "\n",
    "In 2022 my friend [A. J. Jacobs](https://ajjacobs.com/)  set a goal of **walking to space**: climbing a total elevation equal to the distance from the Earth's surface to the top of the atmoshere. [A group](https://www.facebook.com/groups/260966686136038) of about 40 of us joined the quest. The boundary of \"space\" is vague, but the [Kármán line](https://en.wikipedia.org/wiki/K%C3%A1rm%C3%A1n_line) is 100 kilometers; in 2022 I surpassed 100 kilometers of climbing (over 1,100 feet per day), but most years I'm closer to 60 kilometers (about 600 feet per day)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Explorer Tiles\n",
    "\n",
    "\n",
    "The [OpenStreetMap](https://www.openstreetmap.org/) world map is divided into **[explorer tiles](https://www.statshunters.com/faq-10-what-are-explorer-tiles)** of approximately 1 mile square.  Sites like [Veloviewer](https://veloviewer.com), [Statshunter](https://www.statshunters.com/), [RideEveryTile](https://rideeverytile.com/), and [SquadRats](https://squadrats.com/map) challenge bicyclist/hikers to record which tiles they have passed through. The process is gamified to highlight the following statistics:\n",
    "- The largest **square** (an *n* × *n* array of visited tiles). \n",
    "- The maximum **cluster** (a set of contiguous visited tiles, each one bounded on all four sides by visited tiles).\n",
    "- The **total** number of visited tiles.\n",
    " \n",
    "\n",
    "Since I live on a penninsula, it is not easy for me to form a large square, and I sometimes have to work hard to connect different parts of my map into my main cluster (such as connecting San Francisco and Marin across the Golden Gate Bridge). But I have been able to cobble together a cluster that extends from CLoverdale to Monterey. Here are a few key points along the way:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "</style>\n",
       "<table id=\"T_7d259\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_7d259_level0_col0\" class=\"col_heading level0 col0\" >date</th>\n",
       "      <th id=\"T_7d259_level0_col1\" class=\"col_heading level0 col1\" >square</th>\n",
       "      <th id=\"T_7d259_level0_col2\" class=\"col_heading level0 col2\" >cluster</th>\n",
       "      <th id=\"T_7d259_level0_col3\" class=\"col_heading level0 col3\" >total</th>\n",
       "      <th id=\"T_7d259_level0_col4\" class=\"col_heading level0 col4\" >comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row0\" class=\"row_heading level0 row0\" ></th>\n",
       "      <td id=\"T_7d259_row0_col0\" class=\"data row0 col0\" ><a href=\"https://www.statshunters.com/?to=20250101\" rel=\"noopener noreferrer\" target=\"_blank\">01/01/2025</a></td>\n",
       "      <td id=\"T_7d259_row0_col1\" class=\"data row0 col1\" >14</td>\n",
       "      <td id=\"T_7d259_row0_col2\" class=\"data row0 col2\" >1395</td>\n",
       "      <td id=\"T_7d259_row0_col3\" class=\"data row0 col3\" >3520</td>\n",
       "      <td id=\"T_7d259_row0_col4\" class=\"data row0 col4\" >Start of 2025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row1\" class=\"row_heading level0 row1\" ></th>\n",
       "      <td id=\"T_7d259_row1_col0\" class=\"data row1 col0\" ><a href=\"https://www.statshunters.com/?to=20240921\" rel=\"noopener noreferrer\" target=\"_blank\">09/21/2024</a></td>\n",
       "      <td id=\"T_7d259_row1_col1\" class=\"data row1 col1\" >14</td>\n",
       "      <td id=\"T_7d259_row1_col2\" class=\"data row1 col2\" >1394</td>\n",
       "      <td id=\"T_7d259_row1_col3\" class=\"data row1 col3\" >3496</td>\n",
       "      <td id=\"T_7d259_row1_col4\" class=\"data row1 col4\" ><a href=\"https://www.strava.com/activities/12470434052\" rel=\"noopener noreferrer\" target=\"_blank\">Michael J. Fox ride in Sonoma</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row2\" class=\"row_heading level0 row2\" ></th>\n",
       "      <td id=\"T_7d259_row2_col0\" class=\"data row2 col0\" ><a href=\"https://www.statshunters.com/?to=20240428\" rel=\"noopener noreferrer\" target=\"_blank\">04/28/2024</a></td>\n",
       "      <td id=\"T_7d259_row2_col1\" class=\"data row2 col1\" >14</td>\n",
       "      <td id=\"T_7d259_row2_col2\" class=\"data row2 col2\" >1275</td>\n",
       "      <td id=\"T_7d259_row2_col3\" class=\"data row2 col3\" >3382</td>\n",
       "      <td id=\"T_7d259_row2_col4\" class=\"data row2 col4\" ><a href=\"https://www.strava.com/activities/11287081291\" rel=\"noopener noreferrer\" target=\"_blank\">Livermore</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row3\" class=\"row_heading level0 row3\" ></th>\n",
       "      <td id=\"T_7d259_row3_col0\" class=\"data row3 col0\" ><a href=\"https://www.statshunters.com/?to=20240225\" rel=\"noopener noreferrer\" target=\"_blank\">02/25/2024</a></td>\n",
       "      <td id=\"T_7d259_row3_col1\" class=\"data row3 col1\" >14</td>\n",
       "      <td id=\"T_7d259_row3_col2\" class=\"data row3 col2\" >1196</td>\n",
       "      <td id=\"T_7d259_row3_col3\" class=\"data row3 col3\" >3279</td>\n",
       "      <td id=\"T_7d259_row3_col4\" class=\"data row3 col4\" ><a href=\"https://www.strava.com/activities/10838162005\" rel=\"noopener noreferrer\" target=\"_blank\">Expanding through Santa Cruz and to the South</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row4\" class=\"row_heading level0 row4\" ></th>\n",
       "      <td id=\"T_7d259_row4_col0\" class=\"data row4 col0\" ><a href=\"https://www.statshunters.com/?to=20240101\" rel=\"noopener noreferrer\" target=\"_blank\">01/01/2024</a></td>\n",
       "      <td id=\"T_7d259_row4_col1\" class=\"data row4 col1\" >14</td>\n",
       "      <td id=\"T_7d259_row4_col2\" class=\"data row4 col2\" >1056</td>\n",
       "      <td id=\"T_7d259_row4_col3\" class=\"data row4 col3\" >3105</td>\n",
       "      <td id=\"T_7d259_row4_col4\" class=\"data row4 col4\" >Start of 2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row5\" class=\"row_heading level0 row5\" ></th>\n",
       "      <td id=\"T_7d259_row5_col0\" class=\"data row5 col0\" ><a href=\"https://www.statshunters.com/?to=20231208\" rel=\"noopener noreferrer\" target=\"_blank\">12/08/2023</a></td>\n",
       "      <td id=\"T_7d259_row5_col1\" class=\"data row5 col1\" >14</td>\n",
       "      <td id=\"T_7d259_row5_col2\" class=\"data row5 col2\" >1042</td>\n",
       "      <td id=\"T_7d259_row5_col3\" class=\"data row5 col3\" >3084</td>\n",
       "      <td id=\"T_7d259_row5_col4\" class=\"data row5 col4\" ><a href=\"https://www.strava.com/activities/10350071201\" rel=\"noopener noreferrer\" target=\"_blank\">Benicia ride connects East Bay and Napa clusters</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row6\" class=\"row_heading level0 row6\" ></th>\n",
       "      <td id=\"T_7d259_row6_col0\" class=\"data row6 col0\" ><a href=\"https://www.statshunters.com/?to=20231105\" rel=\"noopener noreferrer\" target=\"_blank\">11/05/2023</a></td>\n",
       "      <td id=\"T_7d259_row6_col1\" class=\"data row6 col1\" >14</td>\n",
       "      <td id=\"T_7d259_row6_col2\" class=\"data row6 col2\" >932</td>\n",
       "      <td id=\"T_7d259_row6_col3\" class=\"data row6 col3\" >2914</td>\n",
       "      <td id=\"T_7d259_row6_col4\" class=\"data row6 col4\" ><a href=\"https://www.strava.com/activities/8850905872\" rel=\"noopener noreferrer\" target=\"_blank\">Alum Rock ride gets 14x14 max square</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row7\" class=\"row_heading level0 row7\" ></th>\n",
       "      <td id=\"T_7d259_row7_col0\" class=\"data row7 col0\" ><a href=\"https://www.statshunters.com/?to=20230630\" rel=\"noopener noreferrer\" target=\"_blank\">06/30/2023</a></td>\n",
       "      <td id=\"T_7d259_row7_col1\" class=\"data row7 col1\" >13</td>\n",
       "      <td id=\"T_7d259_row7_col2\" class=\"data row7 col2\" >689</td>\n",
       "      <td id=\"T_7d259_row7_col3\" class=\"data row7 col3\" >2640</td>\n",
       "      <td id=\"T_7d259_row7_col4\" class=\"data row7 col4\" ><a href=\"https://www.strava.com/activities/9298603815\" rel=\"noopener noreferrer\" target=\"_blank\">Rides in east Bay fill in holes</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row8\" class=\"row_heading level0 row8\" ></th>\n",
       "      <td id=\"T_7d259_row8_col0\" class=\"data row8 col0\" ><a href=\"https://www.statshunters.com/?to=20230414\" rel=\"noopener noreferrer\" target=\"_blank\">04/14/2023</a></td>\n",
       "      <td id=\"T_7d259_row8_col1\" class=\"data row8 col1\" >13</td>\n",
       "      <td id=\"T_7d259_row8_col2\" class=\"data row8 col2\" >630</td>\n",
       "      <td id=\"T_7d259_row8_col3\" class=\"data row8 col3\" >2595</td>\n",
       "      <td id=\"T_7d259_row8_col4\" class=\"data row8 col4\" ><a href=\"https://www.strava.com/activities/8891171008\" rel=\"noopener noreferrer\" target=\"_blank\">Black Sands Beach low-tide hike connects Marin to max cluster</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row9\" class=\"row_heading level0 row9\" ></th>\n",
       "      <td id=\"T_7d259_row9_col0\" class=\"data row9 col0\" ><a href=\"https://www.statshunters.com/?to=20230304\" rel=\"noopener noreferrer\" target=\"_blank\">03/04/2023</a></td>\n",
       "      <td id=\"T_7d259_row9_col1\" class=\"data row9 col1\" >13</td>\n",
       "      <td id=\"T_7d259_row9_col2\" class=\"data row9 col2\" >583</td>\n",
       "      <td id=\"T_7d259_row9_col3\" class=\"data row9 col3\" >2574</td>\n",
       "      <td id=\"T_7d259_row9_col4\" class=\"data row9 col4\" ><a href=\"https://www.strava.com/activities/8654437264\" rel=\"noopener noreferrer\" target=\"_blank\">Almaden rides connects Gilroy to max cluster</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row10\" class=\"row_heading level0 row10\" ></th>\n",
       "      <td id=\"T_7d259_row10_col0\" class=\"data row10 col0\" ><a href=\"https://www.statshunters.com/?to=20221022\" rel=\"noopener noreferrer\" target=\"_blank\">10/22/2022</a></td>\n",
       "      <td id=\"T_7d259_row10_col1\" class=\"data row10 col1\" >13</td>\n",
       "      <td id=\"T_7d259_row10_col2\" class=\"data row10 col2\" >396</td>\n",
       "      <td id=\"T_7d259_row10_col3\" class=\"data row10 col3\" >2495</td>\n",
       "      <td id=\"T_7d259_row10_col4\" class=\"data row10 col4\" ><a href=\"https://www.strava.com/activities/8003921626\" rel=\"noopener noreferrer\" target=\"_blank\">Alviso levees to get to 13x13 max square</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row11\" class=\"row_heading level0 row11\" ></th>\n",
       "      <td id=\"T_7d259_row11_col0\" class=\"data row11 col0\" ><a href=\"https://www.statshunters.com/?to=20221016\" rel=\"noopener noreferrer\" target=\"_blank\">10/16/2022</a></td>\n",
       "      <td id=\"T_7d259_row11_col1\" class=\"data row11 col1\" >12</td>\n",
       "      <td id=\"T_7d259_row11_col2\" class=\"data row11 col2\" >393</td>\n",
       "      <td id=\"T_7d259_row11_col3\" class=\"data row11 col3\" >2492</td>\n",
       "      <td id=\"T_7d259_row11_col4\" class=\"data row11 col4\" ><a href=\"https://www.strava.com/activities/7974994605\" rel=\"noopener noreferrer\" target=\"_blank\">Milpitas ride connects East Bay to max cluster</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_7d259_level0_row12\" class=\"row_heading level0 row12\" ></th>\n",
       "      <td id=\"T_7d259_row12_col0\" class=\"data row12 col0\" ><a href=\"https://www.statshunters.com/?to=20220908\" rel=\"noopener noreferrer\" target=\"_blank\">09/08/2022</a></td>\n",
       "      <td id=\"T_7d259_row12_col1\" class=\"data row12 col1\" >11</td>\n",
       "      <td id=\"T_7d259_row12_col2\" class=\"data row12 col2\" >300</td>\n",
       "      <td id=\"T_7d259_row12_col3\" class=\"data row12 col3\" >2487</td>\n",
       "      <td id=\"T_7d259_row12_col4\" class=\"data row12 col4\" >First started tracking tiles</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x121c44ec0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tiles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's my map (as of March 2025), with pink being the largest square, orange the largest cluster, and yellow visited tiles.\n",
    "\n",
    "![](statshunter.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wandering \n",
    "\n",
    "The website [**Wandrer.earth**](https://wandrer.earth) tracks the  distinct roads a user has biked on. It provides a fun incentive to get out and explore new roads. The site is gamified in a way that there is a reward for first reaching 25% of the road-miles in each city, and further rewards for higher percentages.  (You get no credit for repeating a road you've already been on.) \n",
    "\n",
    "The wandrer.earth site does a good job of showing my current status, but it requires clicking around a bit, so I summarize it all in one place here.  Each line gives the **name** of a place (and maybe the **county** it is in), the **total** number of miles of roads and trails in the place, the number of miles I have **done**, the percentage (**pct**) done, the **badge** I have been awarded, and the number of miles to go **to next badge**, or to the next **big badge** (the big badge points are at 25% of the roads in an area (a bonus of 25%) and at 90% of the roads (a bonus of 50%)).\n",
    "\n",
    "I'm proud of several accomplishments on Wandrer.earth:\n",
    "- Got the \"accomplishment\" (25%) for every city in Santa Clara and San Mateo counties (but I'm still missing a few small state parks).\n",
    "- Got the accomplishment for every city ringing the Bay below the Bay Bridge (i.e. San Francisco, down the Peninsula to San Jose, and up to Oakland).\n",
    "- Completed (99%+) every city within 10 miles me, from San Carlos to Los Altos.\n",
    "- Got to 90% of every city within about 15 miles of me on the penninsula, from San Bruno to Cupertino.\n",
    "- Got to 2% of all of California's roads.\n",
    "\n",
    "Here is my map (yellow: 99%, orange: 90%, pink: 50%, purple: 25%; parts North of SF/Oakland not shown):\n",
    "\n",
    "![](wandrer.jpg)\n",
    "\n",
    "## Wandering: Big Places\n",
    "\n",
    "In the following subsections I show my wandrer progress by area:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>county</th>\n",
       "      <th>total</th>\n",
       "      <th>done</th>\n",
       "      <th>pct</th>\n",
       "      <th>badge</th>\n",
       "      <th>to next badge</th>\n",
       "      <th>to big badge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Mateo County</td>\n",
       "      <td>---</td>\n",
       "      <td>2826.05</td>\n",
       "      <td>2,227</td>\n",
       "      <td>78.80%</td>\n",
       "      <td>75%</td>\n",
       "      <td>317 mi to 90% (1,730 points)</td>\n",
       "      <td>317 mi to 90% (1,730 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Santa Clara County</td>\n",
       "      <td>---</td>\n",
       "      <td>7690.85</td>\n",
       "      <td>2,976</td>\n",
       "      <td>38.70%</td>\n",
       "      <td>25%</td>\n",
       "      <td>869 mi to 50% (1,254 points)</td>\n",
       "      <td>3,945 mi to 90% (7,791 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alameda County</td>\n",
       "      <td>---</td>\n",
       "      <td>5802.83</td>\n",
       "      <td>1,454</td>\n",
       "      <td>25.06%</td>\n",
       "      <td>25%</td>\n",
       "      <td>1,447 mi to 50% (1,737 points)</td>\n",
       "      <td>3,768 mi to 90% (6,670 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Marin County</td>\n",
       "      <td>---</td>\n",
       "      <td>2453.18</td>\n",
       "      <td>294</td>\n",
       "      <td>11.97%</td>\n",
       "      <td>none</td>\n",
       "      <td>320 mi to 25% (933 points)</td>\n",
       "      <td>320 mi to 25% (933 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Francisco County</td>\n",
       "      <td>---</td>\n",
       "      <td>1234.85</td>\n",
       "      <td>143</td>\n",
       "      <td>11.60%</td>\n",
       "      <td>none</td>\n",
       "      <td>165 mi to 25% (474 points)</td>\n",
       "      <td>165 mi to 25% (474 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Santa Cruz County</td>\n",
       "      <td>---</td>\n",
       "      <td>2700.36</td>\n",
       "      <td>286</td>\n",
       "      <td>10.58%</td>\n",
       "      <td>none</td>\n",
       "      <td>389 mi to 25% (1,064 points)</td>\n",
       "      <td>389 mi to 25% (1,064 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Napa County</td>\n",
       "      <td>---</td>\n",
       "      <td>1677.57</td>\n",
       "      <td>149</td>\n",
       "      <td>8.90%</td>\n",
       "      <td>none</td>\n",
       "      <td>270 mi to 25% (689 points)</td>\n",
       "      <td>270 mi to 25% (689 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sonoma County</td>\n",
       "      <td>---</td>\n",
       "      <td>4955.30</td>\n",
       "      <td>367</td>\n",
       "      <td>7.40%</td>\n",
       "      <td>none</td>\n",
       "      <td>872 mi to 25% (2,111 points)</td>\n",
       "      <td>872 mi to 25% (2,111 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Contra Costa County</td>\n",
       "      <td>---</td>\n",
       "      <td>5905.56</td>\n",
       "      <td>244</td>\n",
       "      <td>4.14%</td>\n",
       "      <td>none</td>\n",
       "      <td>1,232 mi to 25% (2,708 points)</td>\n",
       "      <td>1,232 mi to 25% (2,708 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>California</td>\n",
       "      <td>---</td>\n",
       "      <td>389799.00</td>\n",
       "      <td>8,638</td>\n",
       "      <td>2.22%</td>\n",
       "      <td>none</td>\n",
       "      <td>88,812 mi to 25% (0.19M points)</td>\n",
       "      <td>88,812 mi to 25% (0.19M points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>USA</td>\n",
       "      <td>---</td>\n",
       "      <td>6459275.00</td>\n",
       "      <td>9,082</td>\n",
       "      <td>0.1406%</td>\n",
       "      <td>none</td>\n",
       "      <td>3,837 mi to 0.2% (3,837 points)</td>\n",
       "      <td>1.6M mi to 25% (3.2M points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Earth</td>\n",
       "      <td>---</td>\n",
       "      <td>46047996.80</td>\n",
       "      <td>9,387</td>\n",
       "      <td>0.0204%</td>\n",
       "      <td>none</td>\n",
       "      <td>36,661 mi to 0.1% (36,661 points)</td>\n",
       "      <td>12M mi to 25% (23M points)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name county        total   done      pct badge  \\\n",
       "      San Mateo County    ---      2826.05  2,227   78.80%   75%   \n",
       "    Santa Clara County    ---      7690.85  2,976   38.70%   25%   \n",
       "        Alameda County    ---      5802.83  1,454   25.06%   25%   \n",
       "          Marin County    ---      2453.18    294   11.97%  none   \n",
       "  San Francisco County    ---      1234.85    143   11.60%  none   \n",
       "     Santa Cruz County    ---      2700.36    286   10.58%  none   \n",
       "           Napa County    ---      1677.57    149    8.90%  none   \n",
       "         Sonoma County    ---      4955.30    367    7.40%  none   \n",
       "   Contra Costa County    ---      5905.56    244    4.14%  none   \n",
       "            California    ---    389799.00  8,638    2.22%  none   \n",
       "                   USA    ---   6459275.00  9,082  0.1406%  none   \n",
       "                 Earth    ---  46047996.80  9,387  0.0204%  none   \n",
       "\n",
       "                      to next badge                     to big badge  \n",
       "       317 mi to 90% (1,730 points)     317 mi to 90% (1,730 points)  \n",
       "       869 mi to 50% (1,254 points)   3,945 mi to 90% (7,791 points)  \n",
       "     1,447 mi to 50% (1,737 points)   3,768 mi to 90% (6,670 points)  \n",
       "         320 mi to 25% (933 points)       320 mi to 25% (933 points)  \n",
       "         165 mi to 25% (474 points)       165 mi to 25% (474 points)  \n",
       "       389 mi to 25% (1,064 points)     389 mi to 25% (1,064 points)  \n",
       "         270 mi to 25% (689 points)       270 mi to 25% (689 points)  \n",
       "       872 mi to 25% (2,111 points)     872 mi to 25% (2,111 points)  \n",
       "     1,232 mi to 25% (2,708 points)   1,232 mi to 25% (2,708 points)  \n",
       "    88,812 mi to 25% (0.19M points)  88,812 mi to 25% (0.19M points)  \n",
       "    3,837 mi to 0.2% (3,837 points)     1.6M mi to 25% (3.2M points)  \n",
       "  36,661 mi to 0.1% (36,661 points)       12M mi to 25% (23M points)  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wandrer(county='---')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wandering: San Mateo County"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>county</th>\n",
       "      <th>total</th>\n",
       "      <th>done</th>\n",
       "      <th>pct</th>\n",
       "      <th>badge</th>\n",
       "      <th>to next badge</th>\n",
       "      <th>to big badge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Atherton</td>\n",
       "      <td>SMC</td>\n",
       "      <td>56.30</td>\n",
       "      <td>56</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>East Palo Alto</td>\n",
       "      <td>SMC</td>\n",
       "      <td>48.30</td>\n",
       "      <td>48</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Emerald Lake Hills</td>\n",
       "      <td>SMC</td>\n",
       "      <td>24.60</td>\n",
       "      <td>25</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kensington Square</td>\n",
       "      <td>SMC</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.6</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Ladera</td>\n",
       "      <td>SMC</td>\n",
       "      <td>8.10</td>\n",
       "      <td>8.1</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Los Trancos OSP</td>\n",
       "      <td>SMC</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.3</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Los Trancos Woods</td>\n",
       "      <td>SMC</td>\n",
       "      <td>5.30</td>\n",
       "      <td>5.3</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Menlo Oaks</td>\n",
       "      <td>SMC</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.5</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>North Fair Oaks</td>\n",
       "      <td>SMC</td>\n",
       "      <td>26.70</td>\n",
       "      <td>27</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Palomar Park</td>\n",
       "      <td>SMC</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Portola Valley</td>\n",
       "      <td>SMC</td>\n",
       "      <td>48.20</td>\n",
       "      <td>48</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sequoia Tract</td>\n",
       "      <td>SMC</td>\n",
       "      <td>11.00</td>\n",
       "      <td>11</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sky Londa</td>\n",
       "      <td>SMC</td>\n",
       "      <td>10.42</td>\n",
       "      <td>10</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>West Menlo Park</td>\n",
       "      <td>SMC</td>\n",
       "      <td>11.20</td>\n",
       "      <td>11</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Windy Hill Preserve</td>\n",
       "      <td>SMC</td>\n",
       "      <td>4.10</td>\n",
       "      <td>4.1</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Woodside</td>\n",
       "      <td>SMC</td>\n",
       "      <td>75.20</td>\n",
       "      <td>75</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Menlo Park</td>\n",
       "      <td>SMC</td>\n",
       "      <td>139.50</td>\n",
       "      <td>139</td>\n",
       "      <td>99.97%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Redwood City</td>\n",
       "      <td>SMC</td>\n",
       "      <td>240.50</td>\n",
       "      <td>240</td>\n",
       "      <td>99.66%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Carlos</td>\n",
       "      <td>SMC</td>\n",
       "      <td>99.00</td>\n",
       "      <td>99</td>\n",
       "      <td>99.52%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Foster City</td>\n",
       "      <td>SMC</td>\n",
       "      <td>150.00</td>\n",
       "      <td>149</td>\n",
       "      <td>99.14%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Burleigh Murray Park</td>\n",
       "      <td>SMC</td>\n",
       "      <td>2.10</td>\n",
       "      <td>2.0</td>\n",
       "      <td>95.08%</td>\n",
       "      <td>90%</td>\n",
       "      <td>0.1 mi to 99% (0.3 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Burlingame</td>\n",
       "      <td>SMC</td>\n",
       "      <td>88.40</td>\n",
       "      <td>83</td>\n",
       "      <td>93.72%</td>\n",
       "      <td>90%</td>\n",
       "      <td>4.7 mi to 99% (14 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Brisbane</td>\n",
       "      <td>SMC</td>\n",
       "      <td>40.90</td>\n",
       "      <td>38</td>\n",
       "      <td>93.60%</td>\n",
       "      <td>90%</td>\n",
       "      <td>2.2 mi to 99% (6.3 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Colma</td>\n",
       "      <td>SMC</td>\n",
       "      <td>13.70</td>\n",
       "      <td>13</td>\n",
       "      <td>92.62%</td>\n",
       "      <td>90%</td>\n",
       "      <td>0.9 mi to 99% (2.2 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Mateo Highlands</td>\n",
       "      <td>SMC</td>\n",
       "      <td>18.00</td>\n",
       "      <td>17</td>\n",
       "      <td>92.43%</td>\n",
       "      <td>90%</td>\n",
       "      <td>1.2 mi to 99% (3.0 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Burlingame Hills</td>\n",
       "      <td>SMC</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.5</td>\n",
       "      <td>92.38%</td>\n",
       "      <td>90%</td>\n",
       "      <td>0.4 mi to 99% (1.0 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Millbrae</td>\n",
       "      <td>SMC</td>\n",
       "      <td>67.80</td>\n",
       "      <td>63</td>\n",
       "      <td>92.31%</td>\n",
       "      <td>90%</td>\n",
       "      <td>4.5 mi to 99% (11 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Mateo</td>\n",
       "      <td>SMC</td>\n",
       "      <td>256.00</td>\n",
       "      <td>236</td>\n",
       "      <td>92.27%</td>\n",
       "      <td>90%</td>\n",
       "      <td>17 mi to 99% (43 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Hillsborough</td>\n",
       "      <td>SMC</td>\n",
       "      <td>85.30</td>\n",
       "      <td>77</td>\n",
       "      <td>90.52%</td>\n",
       "      <td>90%</td>\n",
       "      <td>7.2 mi to 99% (16 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Belmont</td>\n",
       "      <td>SMC</td>\n",
       "      <td>98.10</td>\n",
       "      <td>89</td>\n",
       "      <td>90.43%</td>\n",
       "      <td>90%</td>\n",
       "      <td>8.4 mi to 99% (18 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Bruno</td>\n",
       "      <td>SMC</td>\n",
       "      <td>114.00</td>\n",
       "      <td>103</td>\n",
       "      <td>90.19%</td>\n",
       "      <td>90%</td>\n",
       "      <td>10 mi to 99% (21 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Skyline Ridge OSP</td>\n",
       "      <td>SMC</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.6</td>\n",
       "      <td>75.41%</td>\n",
       "      <td>75%</td>\n",
       "      <td>0.1 mi to 90% (0.5 points)</td>\n",
       "      <td>0.1 mi to 90% (0.5 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Portola Redwoods SP</td>\n",
       "      <td>SMC</td>\n",
       "      <td>2.90</td>\n",
       "      <td>2.1</td>\n",
       "      <td>74.07%</td>\n",
       "      <td>50%</td>\n",
       "      <td>0.0 mi to 75% (0.3 points)</td>\n",
       "      <td>0.5 mi to 90% (1.9 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Coal Creek Preserve</td>\n",
       "      <td>SMC</td>\n",
       "      <td>3.90</td>\n",
       "      <td>2.7</td>\n",
       "      <td>68.74%</td>\n",
       "      <td>50%</td>\n",
       "      <td>0.2 mi to 75% (0.6 points)</td>\n",
       "      <td>0.8 mi to 90% (2.8 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Half Moon Bay State Beach</td>\n",
       "      <td>SMC</td>\n",
       "      <td>4.40</td>\n",
       "      <td>2.9</td>\n",
       "      <td>65.89%</td>\n",
       "      <td>50%</td>\n",
       "      <td>0.4 mi to 75% (0.8 points)</td>\n",
       "      <td>1.1 mi to 90% (3.3 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Montara</td>\n",
       "      <td>SMC</td>\n",
       "      <td>27.80</td>\n",
       "      <td>17</td>\n",
       "      <td>61.15%</td>\n",
       "      <td>50%</td>\n",
       "      <td>3.9 mi to 75% (6.6 points)</td>\n",
       "      <td>8.0 mi to 90% (22 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Moss Beach</td>\n",
       "      <td>SMC</td>\n",
       "      <td>19.70</td>\n",
       "      <td>12</td>\n",
       "      <td>59.66%</td>\n",
       "      <td>50%</td>\n",
       "      <td>3.0 mi to 75% (5.0 points)</td>\n",
       "      <td>6.0 mi to 90% (16 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Russian Ridge Preserve</td>\n",
       "      <td>SMC</td>\n",
       "      <td>12.20</td>\n",
       "      <td>7.3</td>\n",
       "      <td>59.66%</td>\n",
       "      <td>50%</td>\n",
       "      <td>1.9 mi to 75% (3.1 points)</td>\n",
       "      <td>3.7 mi to 90% (9.8 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>El Granada</td>\n",
       "      <td>SMC</td>\n",
       "      <td>49.20</td>\n",
       "      <td>26</td>\n",
       "      <td>53.71%</td>\n",
       "      <td>50%</td>\n",
       "      <td>10 mi to 75% (15 points)</td>\n",
       "      <td>18 mi to 90% (42 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Half Moon Bay</td>\n",
       "      <td>SMC</td>\n",
       "      <td>68.00</td>\n",
       "      <td>34</td>\n",
       "      <td>50.56%</td>\n",
       "      <td>50%</td>\n",
       "      <td>17 mi to 75% (23 points)</td>\n",
       "      <td>27 mi to 90% (61 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Long Ridge Preserve</td>\n",
       "      <td>SMC</td>\n",
       "      <td>11.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>45.10%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.5 mi to 50% (1.1 points)</td>\n",
       "      <td>4.9 mi to 90% (10 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>South San Francisco</td>\n",
       "      <td>SMC</td>\n",
       "      <td>185.30</td>\n",
       "      <td>75</td>\n",
       "      <td>40.36%</td>\n",
       "      <td>25%</td>\n",
       "      <td>18 mi to 50% (27 points)</td>\n",
       "      <td>92 mi to 90% (185 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Purisima Creek Preserve</td>\n",
       "      <td>SMC</td>\n",
       "      <td>16.50</td>\n",
       "      <td>6.4</td>\n",
       "      <td>39.09%</td>\n",
       "      <td>25%</td>\n",
       "      <td>1.8 mi to 50% (2.6 points)</td>\n",
       "      <td>8.4 mi to 90% (17 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Broadmoor</td>\n",
       "      <td>SMC</td>\n",
       "      <td>8.80</td>\n",
       "      <td>3.4</td>\n",
       "      <td>38.26%</td>\n",
       "      <td>25%</td>\n",
       "      <td>1.0 mi to 50% (1.5 points)</td>\n",
       "      <td>4.6 mi to 90% (9.0 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Pacifica</td>\n",
       "      <td>SMC</td>\n",
       "      <td>150.90</td>\n",
       "      <td>56</td>\n",
       "      <td>36.80%</td>\n",
       "      <td>25%</td>\n",
       "      <td>20 mi to 50% (27 points)</td>\n",
       "      <td>80 mi to 90% (156 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Butano State Park</td>\n",
       "      <td>SMC</td>\n",
       "      <td>15.20</td>\n",
       "      <td>4.5</td>\n",
       "      <td>29.28%</td>\n",
       "      <td>25%</td>\n",
       "      <td>3.1 mi to 50% (3.9 points)</td>\n",
       "      <td>9.2 mi to 90% (17 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Bay Area Ridge Trail</td>\n",
       "      <td>SMC</td>\n",
       "      <td>395.60</td>\n",
       "      <td>115</td>\n",
       "      <td>29.11%</td>\n",
       "      <td>25%</td>\n",
       "      <td>83 mi to 50% (102 points)</td>\n",
       "      <td>241 mi to 90% (439 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Daly City</td>\n",
       "      <td>SMC</td>\n",
       "      <td>148.10</td>\n",
       "      <td>43</td>\n",
       "      <td>28.75%</td>\n",
       "      <td>25%</td>\n",
       "      <td>31 mi to 50% (39 points)</td>\n",
       "      <td>91 mi to 90% (165 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>El Corte de Madera OSP</td>\n",
       "      <td>SMC</td>\n",
       "      <td>34.54</td>\n",
       "      <td>9.3</td>\n",
       "      <td>26.85%</td>\n",
       "      <td>25%</td>\n",
       "      <td>8.0 mi to 50% (9.7 points)</td>\n",
       "      <td>22 mi to 90% (39 points)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name county   total done     pct badge  \\\n",
       "                   Atherton    SMC   56.30   56    100%   99%   \n",
       "             East Palo Alto    SMC   48.30   48    100%   99%   \n",
       "         Emerald Lake Hills    SMC   24.60   25    100%   99%   \n",
       "          Kensington Square    SMC    0.60  0.6    100%   99%   \n",
       "                     Ladera    SMC    8.10  8.1    100%   99%   \n",
       "            Los Trancos OSP    SMC    0.30  0.3    100%   99%   \n",
       "          Los Trancos Woods    SMC    5.30  5.3    100%   99%   \n",
       "                 Menlo Oaks    SMC    3.50  3.5    100%   99%   \n",
       "            North Fair Oaks    SMC   26.70   27    100%   99%   \n",
       "               Palomar Park    SMC    4.00  4.0    100%   99%   \n",
       "             Portola Valley    SMC   48.20   48    100%   99%   \n",
       "              Sequoia Tract    SMC   11.00   11    100%   99%   \n",
       "                  Sky Londa    SMC   10.42   10    100%   99%   \n",
       "            West Menlo Park    SMC   11.20   11    100%   99%   \n",
       "        Windy Hill Preserve    SMC    4.10  4.1    100%   99%   \n",
       "                   Woodside    SMC   75.20   75    100%   99%   \n",
       "                 Menlo Park    SMC  139.50  139  99.97%   99%   \n",
       "               Redwood City    SMC  240.50  240  99.66%   99%   \n",
       "                 San Carlos    SMC   99.00   99  99.52%   99%   \n",
       "                Foster City    SMC  150.00  149  99.14%   99%   \n",
       "       Burleigh Murray Park    SMC    2.10  2.0  95.08%   90%   \n",
       "                 Burlingame    SMC   88.40   83  93.72%   90%   \n",
       "                   Brisbane    SMC   40.90   38  93.60%   90%   \n",
       "                      Colma    SMC   13.70   13  92.62%   90%   \n",
       "        San Mateo Highlands    SMC   18.00   17  92.43%   90%   \n",
       "           Burlingame Hills    SMC    6.00  5.5  92.38%   90%   \n",
       "                   Millbrae    SMC   67.80   63  92.31%   90%   \n",
       "                  San Mateo    SMC  256.00  236  92.27%   90%   \n",
       "               Hillsborough    SMC   85.30   77  90.52%   90%   \n",
       "                    Belmont    SMC   98.10   89  90.43%   90%   \n",
       "                  San Bruno    SMC  114.00  103  90.19%   90%   \n",
       "          Skyline Ridge OSP    SMC    0.80  0.6  75.41%   75%   \n",
       "        Portola Redwoods SP    SMC    2.90  2.1  74.07%   50%   \n",
       "        Coal Creek Preserve    SMC    3.90  2.7  68.74%   50%   \n",
       "  Half Moon Bay State Beach    SMC    4.40  2.9  65.89%   50%   \n",
       "                    Montara    SMC   27.80   17  61.15%   50%   \n",
       "                 Moss Beach    SMC   19.70   12  59.66%   50%   \n",
       "     Russian Ridge Preserve    SMC   12.20  7.3  59.66%   50%   \n",
       "                 El Granada    SMC   49.20   26  53.71%   50%   \n",
       "              Half Moon Bay    SMC   68.00   34  50.56%   50%   \n",
       "        Long Ridge Preserve    SMC   11.00  5.0  45.10%   25%   \n",
       "        South San Francisco    SMC  185.30   75  40.36%   25%   \n",
       "    Purisima Creek Preserve    SMC   16.50  6.4  39.09%   25%   \n",
       "                  Broadmoor    SMC    8.80  3.4  38.26%   25%   \n",
       "                   Pacifica    SMC  150.90   56  36.80%   25%   \n",
       "          Butano State Park    SMC   15.20  4.5  29.28%   25%   \n",
       "       Bay Area Ridge Trail    SMC  395.60  115  29.11%   25%   \n",
       "                  Daly City    SMC  148.10   43  28.75%   25%   \n",
       "     El Corte de Madera OSP    SMC   34.54  9.3  26.85%   25%   \n",
       "\n",
       "                 to next badge                  to big badge  \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "                                                              \n",
       "    0.1 mi to 99% (0.3 points)                                \n",
       "     4.7 mi to 99% (14 points)                                \n",
       "    2.2 mi to 99% (6.3 points)                                \n",
       "    0.9 mi to 99% (2.2 points)                                \n",
       "    1.2 mi to 99% (3.0 points)                                \n",
       "    0.4 mi to 99% (1.0 points)                                \n",
       "     4.5 mi to 99% (11 points)                                \n",
       "      17 mi to 99% (43 points)                                \n",
       "     7.2 mi to 99% (16 points)                                \n",
       "     8.4 mi to 99% (18 points)                                \n",
       "      10 mi to 99% (21 points)                                \n",
       "    0.1 mi to 90% (0.5 points)    0.1 mi to 90% (0.5 points)  \n",
       "    0.0 mi to 75% (0.3 points)    0.5 mi to 90% (1.9 points)  \n",
       "    0.2 mi to 75% (0.6 points)    0.8 mi to 90% (2.8 points)  \n",
       "    0.4 mi to 75% (0.8 points)    1.1 mi to 90% (3.3 points)  \n",
       "    3.9 mi to 75% (6.6 points)     8.0 mi to 90% (22 points)  \n",
       "    3.0 mi to 75% (5.0 points)     6.0 mi to 90% (16 points)  \n",
       "    1.9 mi to 75% (3.1 points)    3.7 mi to 90% (9.8 points)  \n",
       "      10 mi to 75% (15 points)      18 mi to 90% (42 points)  \n",
       "      17 mi to 75% (23 points)      27 mi to 90% (61 points)  \n",
       "    0.5 mi to 50% (1.1 points)     4.9 mi to 90% (10 points)  \n",
       "      18 mi to 50% (27 points)     92 mi to 90% (185 points)  \n",
       "    1.8 mi to 50% (2.6 points)     8.4 mi to 90% (17 points)  \n",
       "    1.0 mi to 50% (1.5 points)    4.6 mi to 90% (9.0 points)  \n",
       "      20 mi to 50% (27 points)     80 mi to 90% (156 points)  \n",
       "    3.1 mi to 50% (3.9 points)     9.2 mi to 90% (17 points)  \n",
       "     83 mi to 50% (102 points)    241 mi to 90% (439 points)  \n",
       "      31 mi to 50% (39 points)     91 mi to 90% (165 points)  \n",
       "    8.0 mi to 50% (9.7 points)      22 mi to 90% (39 points)  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wandrer(county='SMC')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wandering: Santa Clara County"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>county</th>\n",
       "      <th>total</th>\n",
       "      <th>done</th>\n",
       "      <th>pct</th>\n",
       "      <th>badge</th>\n",
       "      <th>to next badge</th>\n",
       "      <th>to big badge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Foothills OS Preserve</td>\n",
       "      <td>SCC</td>\n",
       "      <td>1.10</td>\n",
       "      <td>1.1</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Stanford</td>\n",
       "      <td>SCC</td>\n",
       "      <td>82.53</td>\n",
       "      <td>83</td>\n",
       "      <td>100%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Loyola</td>\n",
       "      <td>SCC</td>\n",
       "      <td>18.30</td>\n",
       "      <td>18</td>\n",
       "      <td>99.94%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Los Altos</td>\n",
       "      <td>SCC</td>\n",
       "      <td>138.20</td>\n",
       "      <td>138</td>\n",
       "      <td>99.87%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Palo Alto</td>\n",
       "      <td>SCC</td>\n",
       "      <td>297.20</td>\n",
       "      <td>296</td>\n",
       "      <td>99.52%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Los Altos Hills</td>\n",
       "      <td>SCC</td>\n",
       "      <td>91.30</td>\n",
       "      <td>91</td>\n",
       "      <td>99.38%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mountain View</td>\n",
       "      <td>SCC</td>\n",
       "      <td>208.10</td>\n",
       "      <td>206</td>\n",
       "      <td>99.19%</td>\n",
       "      <td>99%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Monte Sereno</td>\n",
       "      <td>SCC</td>\n",
       "      <td>20.40</td>\n",
       "      <td>19</td>\n",
       "      <td>92.18%</td>\n",
       "      <td>90%</td>\n",
       "      <td>1.4 mi to 99% (3.4 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Cupertino</td>\n",
       "      <td>SCC</td>\n",
       "      <td>172.00</td>\n",
       "      <td>156</td>\n",
       "      <td>90.72%</td>\n",
       "      <td>90%</td>\n",
       "      <td>14 mi to 99% (31 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Saratoga</td>\n",
       "      <td>SCC</td>\n",
       "      <td>180.00</td>\n",
       "      <td>162</td>\n",
       "      <td>90.16%</td>\n",
       "      <td>90%</td>\n",
       "      <td>16 mi to 99% (34 points)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Francisco Bay Trail</td>\n",
       "      <td>SCC</td>\n",
       "      <td>260.80</td>\n",
       "      <td>184</td>\n",
       "      <td>70.71%</td>\n",
       "      <td>50%</td>\n",
       "      <td>11 mi to 75% (37 points)</td>\n",
       "      <td>50 mi to 90% (181 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sunnyvale</td>\n",
       "      <td>SCC</td>\n",
       "      <td>357.00</td>\n",
       "      <td>244</td>\n",
       "      <td>68.34%</td>\n",
       "      <td>50%</td>\n",
       "      <td>24 mi to 75% (59 points)</td>\n",
       "      <td>77 mi to 90% (256 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Los Gatos</td>\n",
       "      <td>SCC</td>\n",
       "      <td>148.00</td>\n",
       "      <td>88</td>\n",
       "      <td>59.19%</td>\n",
       "      <td>50%</td>\n",
       "      <td>23 mi to 75% (38 points)</td>\n",
       "      <td>46 mi to 90% (120 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Castle Rock State Park</td>\n",
       "      <td>SCC</td>\n",
       "      <td>11.20</td>\n",
       "      <td>5.7</td>\n",
       "      <td>51.20%</td>\n",
       "      <td>50%</td>\n",
       "      <td>2.7 mi to 75% (3.8 points)</td>\n",
       "      <td>4.3 mi to 90% (9.9 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Edenvale</td>\n",
       "      <td>SCC</td>\n",
       "      <td>30.00</td>\n",
       "      <td>14</td>\n",
       "      <td>47.80%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.7 mi to 50% (2.2 points)</td>\n",
       "      <td>13 mi to 90% (28 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Gardner</td>\n",
       "      <td>SCC</td>\n",
       "      <td>23.40</td>\n",
       "      <td>11</td>\n",
       "      <td>46.93%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.7 mi to 50% (1.9 points)</td>\n",
       "      <td>10 mi to 90% (22 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Milpitas</td>\n",
       "      <td>SCC</td>\n",
       "      <td>224.00</td>\n",
       "      <td>84</td>\n",
       "      <td>37.36%</td>\n",
       "      <td>25%</td>\n",
       "      <td>28 mi to 50% (40 points)</td>\n",
       "      <td>118 mi to 90% (230 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Spartan Keyes</td>\n",
       "      <td>SCC</td>\n",
       "      <td>64.30</td>\n",
       "      <td>24</td>\n",
       "      <td>36.59%</td>\n",
       "      <td>25%</td>\n",
       "      <td>8.6 mi to 50% (12 points)</td>\n",
       "      <td>34 mi to 90% (66 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Willow Glen</td>\n",
       "      <td>SCC</td>\n",
       "      <td>81.60</td>\n",
       "      <td>30</td>\n",
       "      <td>36.23%</td>\n",
       "      <td>25%</td>\n",
       "      <td>11 mi to 50% (15 points)</td>\n",
       "      <td>44 mi to 90% (85 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Communications Hill</td>\n",
       "      <td>SCC</td>\n",
       "      <td>27.80</td>\n",
       "      <td>9.8</td>\n",
       "      <td>35.31%</td>\n",
       "      <td>25%</td>\n",
       "      <td>4.1 mi to 50% (5.5 points)</td>\n",
       "      <td>15 mi to 90% (29 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Santa Clara</td>\n",
       "      <td>SCC</td>\n",
       "      <td>348.00</td>\n",
       "      <td>123</td>\n",
       "      <td>35.26%</td>\n",
       "      <td>25%</td>\n",
       "      <td>51 mi to 50% (69 points)</td>\n",
       "      <td>190 mi to 90% (364 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Parkview</td>\n",
       "      <td>SCC</td>\n",
       "      <td>42.50</td>\n",
       "      <td>14</td>\n",
       "      <td>34.07%</td>\n",
       "      <td>25%</td>\n",
       "      <td>6.8 mi to 50% (8.9 points)</td>\n",
       "      <td>24 mi to 90% (45 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Seven Trees</td>\n",
       "      <td>SCC</td>\n",
       "      <td>40.90</td>\n",
       "      <td>14</td>\n",
       "      <td>34.06%</td>\n",
       "      <td>25%</td>\n",
       "      <td>6.5 mi to 50% (8.6 points)</td>\n",
       "      <td>23 mi to 90% (43 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Branham</td>\n",
       "      <td>SCC</td>\n",
       "      <td>44.00</td>\n",
       "      <td>15</td>\n",
       "      <td>33.21%</td>\n",
       "      <td>25%</td>\n",
       "      <td>7.4 mi to 50% (9.6 points)</td>\n",
       "      <td>25 mi to 90% (47 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Martin</td>\n",
       "      <td>SCC</td>\n",
       "      <td>35.30</td>\n",
       "      <td>11</td>\n",
       "      <td>31.41%</td>\n",
       "      <td>25%</td>\n",
       "      <td>6.6 mi to 50% (8.3 points)</td>\n",
       "      <td>21 mi to 90% (38 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Willow Glen South</td>\n",
       "      <td>SCC</td>\n",
       "      <td>63.30</td>\n",
       "      <td>20</td>\n",
       "      <td>31.02%</td>\n",
       "      <td>25%</td>\n",
       "      <td>12 mi to 50% (15 points)</td>\n",
       "      <td>37 mi to 90% (69 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Forest of Nisene Marks SP</td>\n",
       "      <td>SCC</td>\n",
       "      <td>44.00</td>\n",
       "      <td>14</td>\n",
       "      <td>30.70%</td>\n",
       "      <td>25%</td>\n",
       "      <td>8.5 mi to 50% (11 points)</td>\n",
       "      <td>26 mi to 90% (48 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Campbell</td>\n",
       "      <td>SCC</td>\n",
       "      <td>119.00</td>\n",
       "      <td>36</td>\n",
       "      <td>30.48%</td>\n",
       "      <td>25%</td>\n",
       "      <td>23 mi to 50% (29 points)</td>\n",
       "      <td>71 mi to 90% (130 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Jose</td>\n",
       "      <td>SCC</td>\n",
       "      <td>2618.70</td>\n",
       "      <td>749</td>\n",
       "      <td>28.59%</td>\n",
       "      <td>25%</td>\n",
       "      <td>561 mi to 50% (692 points)</td>\n",
       "      <td>1,608 mi to 90% (2,917 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Gilroy</td>\n",
       "      <td>SCC</td>\n",
       "      <td>188.90</td>\n",
       "      <td>51</td>\n",
       "      <td>26.88%</td>\n",
       "      <td>25%</td>\n",
       "      <td>44 mi to 50% (53 points)</td>\n",
       "      <td>119 mi to 90% (214 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Morgan Hill</td>\n",
       "      <td>SCC</td>\n",
       "      <td>198.00</td>\n",
       "      <td>52</td>\n",
       "      <td>26.06%</td>\n",
       "      <td>25%</td>\n",
       "      <td>47 mi to 50% (57 points)</td>\n",
       "      <td>127 mi to 90% (226 points)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name county    total done     pct badge  \\\n",
       "      Foothills OS Preserve    SCC     1.10  1.1    100%   99%   \n",
       "                   Stanford    SCC    82.53   83    100%   99%   \n",
       "                     Loyola    SCC    18.30   18  99.94%   99%   \n",
       "                  Los Altos    SCC   138.20  138  99.87%   99%   \n",
       "                  Palo Alto    SCC   297.20  296  99.52%   99%   \n",
       "            Los Altos Hills    SCC    91.30   91  99.38%   99%   \n",
       "              Mountain View    SCC   208.10  206  99.19%   99%   \n",
       "               Monte Sereno    SCC    20.40   19  92.18%   90%   \n",
       "                  Cupertino    SCC   172.00  156  90.72%   90%   \n",
       "                   Saratoga    SCC   180.00  162  90.16%   90%   \n",
       "    San Francisco Bay Trail    SCC   260.80  184  70.71%   50%   \n",
       "                  Sunnyvale    SCC   357.00  244  68.34%   50%   \n",
       "                  Los Gatos    SCC   148.00   88  59.19%   50%   \n",
       "     Castle Rock State Park    SCC    11.20  5.7  51.20%   50%   \n",
       "                   Edenvale    SCC    30.00   14  47.80%   25%   \n",
       "                    Gardner    SCC    23.40   11  46.93%   25%   \n",
       "                   Milpitas    SCC   224.00   84  37.36%   25%   \n",
       "              Spartan Keyes    SCC    64.30   24  36.59%   25%   \n",
       "                Willow Glen    SCC    81.60   30  36.23%   25%   \n",
       "        Communications Hill    SCC    27.80  9.8  35.31%   25%   \n",
       "                Santa Clara    SCC   348.00  123  35.26%   25%   \n",
       "                   Parkview    SCC    42.50   14  34.07%   25%   \n",
       "                Seven Trees    SCC    40.90   14  34.06%   25%   \n",
       "                    Branham    SCC    44.00   15  33.21%   25%   \n",
       "                 San Martin    SCC    35.30   11  31.41%   25%   \n",
       "          Willow Glen South    SCC    63.30   20  31.02%   25%   \n",
       "  Forest of Nisene Marks SP    SCC    44.00   14  30.70%   25%   \n",
       "                   Campbell    SCC   119.00   36  30.48%   25%   \n",
       "                   San Jose    SCC  2618.70  749  28.59%   25%   \n",
       "                     Gilroy    SCC   188.90   51  26.88%   25%   \n",
       "                Morgan Hill    SCC   198.00   52  26.06%   25%   \n",
       "\n",
       "                 to next badge                    to big badge  \n",
       "                                                                \n",
       "                                                                \n",
       "                                                                \n",
       "                                                                \n",
       "                                                                \n",
       "                                                                \n",
       "                                                                \n",
       "    1.4 mi to 99% (3.4 points)                                  \n",
       "      14 mi to 99% (31 points)                                  \n",
       "      16 mi to 99% (34 points)                                  \n",
       "      11 mi to 75% (37 points)       50 mi to 90% (181 points)  \n",
       "      24 mi to 75% (59 points)       77 mi to 90% (256 points)  \n",
       "      23 mi to 75% (38 points)       46 mi to 90% (120 points)  \n",
       "    2.7 mi to 75% (3.8 points)      4.3 mi to 90% (9.9 points)  \n",
       "    0.7 mi to 50% (2.2 points)        13 mi to 90% (28 points)  \n",
       "    0.7 mi to 50% (1.9 points)        10 mi to 90% (22 points)  \n",
       "      28 mi to 50% (40 points)      118 mi to 90% (230 points)  \n",
       "     8.6 mi to 50% (12 points)        34 mi to 90% (66 points)  \n",
       "      11 mi to 50% (15 points)        44 mi to 90% (85 points)  \n",
       "    4.1 mi to 50% (5.5 points)        15 mi to 90% (29 points)  \n",
       "      51 mi to 50% (69 points)      190 mi to 90% (364 points)  \n",
       "    6.8 mi to 50% (8.9 points)        24 mi to 90% (45 points)  \n",
       "    6.5 mi to 50% (8.6 points)        23 mi to 90% (43 points)  \n",
       "    7.4 mi to 50% (9.6 points)        25 mi to 90% (47 points)  \n",
       "    6.6 mi to 50% (8.3 points)        21 mi to 90% (38 points)  \n",
       "      12 mi to 50% (15 points)        37 mi to 90% (69 points)  \n",
       "     8.5 mi to 50% (11 points)        26 mi to 90% (48 points)  \n",
       "      23 mi to 50% (29 points)       71 mi to 90% (130 points)  \n",
       "    561 mi to 50% (692 points)  1,608 mi to 90% (2,917 points)  \n",
       "      44 mi to 50% (53 points)      119 mi to 90% (214 points)  \n",
       "      47 mi to 50% (57 points)      127 mi to 90% (226 points)  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wandrer(county='SCC')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wandering: Alameda County"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>county</th>\n",
       "      <th>total</th>\n",
       "      <th>done</th>\n",
       "      <th>pct</th>\n",
       "      <th>badge</th>\n",
       "      <th>to next badge</th>\n",
       "      <th>to big badge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Newark</td>\n",
       "      <td>ALA</td>\n",
       "      <td>147.00</td>\n",
       "      <td>100</td>\n",
       "      <td>68.00%</td>\n",
       "      <td>50%</td>\n",
       "      <td>10 mi to 75% (25 points)</td>\n",
       "      <td>32 mi to 90% (106 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Hayward Acres</td>\n",
       "      <td>ALA</td>\n",
       "      <td>3.50</td>\n",
       "      <td>1.5</td>\n",
       "      <td>43.53%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.2 mi to 50% (0.4 points)</td>\n",
       "      <td>1.6 mi to 90% (3.4 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Lorenzo</td>\n",
       "      <td>ALA</td>\n",
       "      <td>55.50</td>\n",
       "      <td>23</td>\n",
       "      <td>40.95%</td>\n",
       "      <td>25%</td>\n",
       "      <td>5.0 mi to 50% (7.8 points)</td>\n",
       "      <td>27 mi to 90% (55 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Ashland</td>\n",
       "      <td>ALA</td>\n",
       "      <td>35.10</td>\n",
       "      <td>13</td>\n",
       "      <td>36.49%</td>\n",
       "      <td>25%</td>\n",
       "      <td>4.7 mi to 50% (6.5 points)</td>\n",
       "      <td>19 mi to 90% (36 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fremont</td>\n",
       "      <td>ALA</td>\n",
       "      <td>780.20</td>\n",
       "      <td>278</td>\n",
       "      <td>35.58%</td>\n",
       "      <td>25%</td>\n",
       "      <td>113 mi to 50% (152 points)</td>\n",
       "      <td>425 mi to 90% (815 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Union City</td>\n",
       "      <td>ALA</td>\n",
       "      <td>208.80</td>\n",
       "      <td>70</td>\n",
       "      <td>33.36%</td>\n",
       "      <td>25%</td>\n",
       "      <td>35 mi to 50% (45 points)</td>\n",
       "      <td>118 mi to 90% (223 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Hayward</td>\n",
       "      <td>ALA</td>\n",
       "      <td>444.50</td>\n",
       "      <td>148</td>\n",
       "      <td>33.24%</td>\n",
       "      <td>25%</td>\n",
       "      <td>74 mi to 50% (97 points)</td>\n",
       "      <td>252 mi to 90% (475 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fairview</td>\n",
       "      <td>ALA</td>\n",
       "      <td>34.40</td>\n",
       "      <td>10</td>\n",
       "      <td>29.18%</td>\n",
       "      <td>25%</td>\n",
       "      <td>7.2 mi to 50% (8.9 points)</td>\n",
       "      <td>21 mi to 90% (38 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Leandro</td>\n",
       "      <td>ALA</td>\n",
       "      <td>230.60</td>\n",
       "      <td>65</td>\n",
       "      <td>28.18%</td>\n",
       "      <td>25%</td>\n",
       "      <td>50 mi to 50% (62 points)</td>\n",
       "      <td>143 mi to 90% (258 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Cherryland</td>\n",
       "      <td>ALA</td>\n",
       "      <td>20.90</td>\n",
       "      <td>5.8</td>\n",
       "      <td>27.97%</td>\n",
       "      <td>25%</td>\n",
       "      <td>4.6 mi to 50% (5.6 points)</td>\n",
       "      <td>13 mi to 90% (23 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alameda</td>\n",
       "      <td>ALA</td>\n",
       "      <td>206.70</td>\n",
       "      <td>57</td>\n",
       "      <td>27.36%</td>\n",
       "      <td>25%</td>\n",
       "      <td>47 mi to 50% (57 points)</td>\n",
       "      <td>129 mi to 90% (233 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Dublin</td>\n",
       "      <td>ALA</td>\n",
       "      <td>225.94</td>\n",
       "      <td>61</td>\n",
       "      <td>26.84%</td>\n",
       "      <td>25%</td>\n",
       "      <td>52 mi to 50% (64 points)</td>\n",
       "      <td>143 mi to 90% (256 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Castro Valley</td>\n",
       "      <td>ALA</td>\n",
       "      <td>192.50</td>\n",
       "      <td>51</td>\n",
       "      <td>26.48%</td>\n",
       "      <td>25%</td>\n",
       "      <td>45 mi to 50% (55 points)</td>\n",
       "      <td>122 mi to 90% (219 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Oakland</td>\n",
       "      <td>ALA</td>\n",
       "      <td>272.74</td>\n",
       "      <td>71</td>\n",
       "      <td>25.94%</td>\n",
       "      <td>25%</td>\n",
       "      <td>66 mi to 50% (79 points)</td>\n",
       "      <td>175 mi to 90% (311 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Ramon</td>\n",
       "      <td>ALA</td>\n",
       "      <td>306.46</td>\n",
       "      <td>29</td>\n",
       "      <td>9.36%</td>\n",
       "      <td>none</td>\n",
       "      <td>48 mi to 25% (125 points)</td>\n",
       "      <td>48 mi to 25% (125 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Berkeley</td>\n",
       "      <td>ALA</td>\n",
       "      <td>260.30</td>\n",
       "      <td>20</td>\n",
       "      <td>7.84%</td>\n",
       "      <td>none</td>\n",
       "      <td>45 mi to 25% (110 points)</td>\n",
       "      <td>45 mi to 25% (110 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Emeryville</td>\n",
       "      <td>ALA</td>\n",
       "      <td>28.10</td>\n",
       "      <td>2.2</td>\n",
       "      <td>7.72%</td>\n",
       "      <td>none</td>\n",
       "      <td>4.9 mi to 25% (12 points)</td>\n",
       "      <td>4.9 mi to 25% (12 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Pleasonton</td>\n",
       "      <td>ALA</td>\n",
       "      <td>344.91</td>\n",
       "      <td>26</td>\n",
       "      <td>7.52%</td>\n",
       "      <td>none</td>\n",
       "      <td>60 mi to 25% (147 points)</td>\n",
       "      <td>60 mi to 25% (147 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Albany</td>\n",
       "      <td>ALA</td>\n",
       "      <td>42.70</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.96%</td>\n",
       "      <td>none</td>\n",
       "      <td>7.7 mi to 25% (18 points)</td>\n",
       "      <td>7.7 mi to 25% (18 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Livermore</td>\n",
       "      <td>ALA</td>\n",
       "      <td>448.52</td>\n",
       "      <td>24</td>\n",
       "      <td>5.46%</td>\n",
       "      <td>none</td>\n",
       "      <td>88 mi to 25% (200 points)</td>\n",
       "      <td>88 mi to 25% (200 points)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           name county   total done     pct badge  \\\n",
       "         Newark    ALA  147.00  100  68.00%   50%   \n",
       "  Hayward Acres    ALA    3.50  1.5  43.53%   25%   \n",
       "    San Lorenzo    ALA   55.50   23  40.95%   25%   \n",
       "        Ashland    ALA   35.10   13  36.49%   25%   \n",
       "        Fremont    ALA  780.20  278  35.58%   25%   \n",
       "     Union City    ALA  208.80   70  33.36%   25%   \n",
       "        Hayward    ALA  444.50  148  33.24%   25%   \n",
       "       Fairview    ALA   34.40   10  29.18%   25%   \n",
       "    San Leandro    ALA  230.60   65  28.18%   25%   \n",
       "     Cherryland    ALA   20.90  5.8  27.97%   25%   \n",
       "        Alameda    ALA  206.70   57  27.36%   25%   \n",
       "         Dublin    ALA  225.94   61  26.84%   25%   \n",
       "  Castro Valley    ALA  192.50   51  26.48%   25%   \n",
       "        Oakland    ALA  272.74   71  25.94%   25%   \n",
       "      San Ramon    ALA  306.46   29   9.36%  none   \n",
       "       Berkeley    ALA  260.30   20   7.84%  none   \n",
       "     Emeryville    ALA   28.10  2.2   7.72%  none   \n",
       "     Pleasonton    ALA  344.91   26   7.52%  none   \n",
       "         Albany    ALA   42.70  3.0   6.96%  none   \n",
       "      Livermore    ALA  448.52   24   5.46%  none   \n",
       "\n",
       "                 to next badge                  to big badge  \n",
       "      10 mi to 75% (25 points)     32 mi to 90% (106 points)  \n",
       "    0.2 mi to 50% (0.4 points)    1.6 mi to 90% (3.4 points)  \n",
       "    5.0 mi to 50% (7.8 points)      27 mi to 90% (55 points)  \n",
       "    4.7 mi to 50% (6.5 points)      19 mi to 90% (36 points)  \n",
       "    113 mi to 50% (152 points)    425 mi to 90% (815 points)  \n",
       "      35 mi to 50% (45 points)    118 mi to 90% (223 points)  \n",
       "      74 mi to 50% (97 points)    252 mi to 90% (475 points)  \n",
       "    7.2 mi to 50% (8.9 points)      21 mi to 90% (38 points)  \n",
       "      50 mi to 50% (62 points)    143 mi to 90% (258 points)  \n",
       "    4.6 mi to 50% (5.6 points)      13 mi to 90% (23 points)  \n",
       "      47 mi to 50% (57 points)    129 mi to 90% (233 points)  \n",
       "      52 mi to 50% (64 points)    143 mi to 90% (256 points)  \n",
       "      45 mi to 50% (55 points)    122 mi to 90% (219 points)  \n",
       "      66 mi to 50% (79 points)    175 mi to 90% (311 points)  \n",
       "     48 mi to 25% (125 points)     48 mi to 25% (125 points)  \n",
       "     45 mi to 25% (110 points)     45 mi to 25% (110 points)  \n",
       "     4.9 mi to 25% (12 points)     4.9 mi to 25% (12 points)  \n",
       "     60 mi to 25% (147 points)     60 mi to 25% (147 points)  \n",
       "     7.7 mi to 25% (18 points)     7.7 mi to 25% (18 points)  \n",
       "     88 mi to 25% (200 points)     88 mi to 25% (200 points)  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wandrer(county='ALA')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wandering: San Francisco County"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>county</th>\n",
       "      <th>total</th>\n",
       "      <th>done</th>\n",
       "      <th>pct</th>\n",
       "      <th>badge</th>\n",
       "      <th>to next badge</th>\n",
       "      <th>to big badge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Dogpatch</td>\n",
       "      <td>SFC</td>\n",
       "      <td>5.10</td>\n",
       "      <td>3.1</td>\n",
       "      <td>61.04%</td>\n",
       "      <td>50%</td>\n",
       "      <td>0.7 mi to 75% (1.2 points)</td>\n",
       "      <td>1.5 mi to 90% (4.0 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>South Beach</td>\n",
       "      <td>SFC</td>\n",
       "      <td>5.53</td>\n",
       "      <td>3.3</td>\n",
       "      <td>59.00%</td>\n",
       "      <td>50%</td>\n",
       "      <td>0.9 mi to 75% (1.4 points)</td>\n",
       "      <td>1.7 mi to 90% (4.5 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>India Basin</td>\n",
       "      <td>SFC</td>\n",
       "      <td>6.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>57.57%</td>\n",
       "      <td>50%</td>\n",
       "      <td>1.0 mi to 75% (1.6 points)</td>\n",
       "      <td>1.9 mi to 90% (4.9 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Rincon Hill</td>\n",
       "      <td>SFC</td>\n",
       "      <td>3.49</td>\n",
       "      <td>1.6</td>\n",
       "      <td>46.83%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.1 mi to 50% (0.3 points)</td>\n",
       "      <td>1.5 mi to 90% (3.3 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Presidio Terrace</td>\n",
       "      <td>SFC</td>\n",
       "      <td>2.80</td>\n",
       "      <td>1.2</td>\n",
       "      <td>43.90%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.2 mi to 50% (0.3 points)</td>\n",
       "      <td>1.3 mi to 90% (2.7 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fisherman's Wharf</td>\n",
       "      <td>SFC</td>\n",
       "      <td>6.27</td>\n",
       "      <td>2.7</td>\n",
       "      <td>43.20%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.4 mi to 50% (0.7 points)</td>\n",
       "      <td>2.9 mi to 90% (6.1 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Northern Waterfront</td>\n",
       "      <td>SFC</td>\n",
       "      <td>6.15</td>\n",
       "      <td>2.6</td>\n",
       "      <td>41.48%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.5 mi to 50% (0.8 points)</td>\n",
       "      <td>3.0 mi to 90% (6.1 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Lincoln Park</td>\n",
       "      <td>SFC</td>\n",
       "      <td>4.50</td>\n",
       "      <td>1.8</td>\n",
       "      <td>39.60%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.5 mi to 50% (0.7 points)</td>\n",
       "      <td>2.3 mi to 90% (4.5 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Lake Street</td>\n",
       "      <td>SFC</td>\n",
       "      <td>3.90</td>\n",
       "      <td>1.4</td>\n",
       "      <td>36.80%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.5 mi to 50% (0.7 points)</td>\n",
       "      <td>2.1 mi to 90% (4.0 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Central Waterfront</td>\n",
       "      <td>SFC</td>\n",
       "      <td>11.67</td>\n",
       "      <td>4.2</td>\n",
       "      <td>35.99%</td>\n",
       "      <td>25%</td>\n",
       "      <td>1.6 mi to 50% (2.2 points)</td>\n",
       "      <td>6.3 mi to 90% (12 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Hunters Point</td>\n",
       "      <td>SFC</td>\n",
       "      <td>8.35</td>\n",
       "      <td>3.0</td>\n",
       "      <td>35.38%</td>\n",
       "      <td>25%</td>\n",
       "      <td>1.2 mi to 50% (1.6 points)</td>\n",
       "      <td>4.6 mi to 90% (8.7 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Candkestick Point Sra</td>\n",
       "      <td>SFC</td>\n",
       "      <td>12.39</td>\n",
       "      <td>4.2</td>\n",
       "      <td>34.10%</td>\n",
       "      <td>25%</td>\n",
       "      <td>2.0 mi to 50% (2.6 points)</td>\n",
       "      <td>6.9 mi to 90% (13 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Aquatic Park Fort Mason</td>\n",
       "      <td>SFC</td>\n",
       "      <td>4.41</td>\n",
       "      <td>1.5</td>\n",
       "      <td>34.04%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.7 mi to 50% (0.9 points)</td>\n",
       "      <td>2.5 mi to 90% (4.7 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Little Hollywood</td>\n",
       "      <td>SFC</td>\n",
       "      <td>3.70</td>\n",
       "      <td>1.1</td>\n",
       "      <td>30.74%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.7 mi to 50% (0.9 points)</td>\n",
       "      <td>2.2 mi to 90% (4.0 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Financial District</td>\n",
       "      <td>SFC</td>\n",
       "      <td>11.43</td>\n",
       "      <td>3.5</td>\n",
       "      <td>30.57%</td>\n",
       "      <td>25%</td>\n",
       "      <td>2.2 mi to 50% (2.8 points)</td>\n",
       "      <td>6.8 mi to 90% (13 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Bret Harte</td>\n",
       "      <td>SFC</td>\n",
       "      <td>9.03</td>\n",
       "      <td>2.8</td>\n",
       "      <td>30.49%</td>\n",
       "      <td>25%</td>\n",
       "      <td>1.8 mi to 50% (2.2 points)</td>\n",
       "      <td>5.4 mi to 90% (9.9 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Bayview</td>\n",
       "      <td>SFC</td>\n",
       "      <td>25.63</td>\n",
       "      <td>7.8</td>\n",
       "      <td>30.44%</td>\n",
       "      <td>25%</td>\n",
       "      <td>5.0 mi to 50% (6.3 points)</td>\n",
       "      <td>15 mi to 90% (28 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mission Bay</td>\n",
       "      <td>SFC</td>\n",
       "      <td>16.00</td>\n",
       "      <td>4.8</td>\n",
       "      <td>30.00%</td>\n",
       "      <td>25%</td>\n",
       "      <td>3.2 mi to 50% (4.0 points)</td>\n",
       "      <td>9.6 mi to 90% (18 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Golden Gate Park</td>\n",
       "      <td>SFC</td>\n",
       "      <td>40.80</td>\n",
       "      <td>12</td>\n",
       "      <td>29.40%</td>\n",
       "      <td>25%</td>\n",
       "      <td>8.4 mi to 50% (10 points)</td>\n",
       "      <td>25 mi to 90% (45 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Seacliff</td>\n",
       "      <td>SFC</td>\n",
       "      <td>4.10</td>\n",
       "      <td>1.2</td>\n",
       "      <td>29.30%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.8 mi to 50% (1.1 points)</td>\n",
       "      <td>2.5 mi to 90% (4.5 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Presidio National Park</td>\n",
       "      <td>SFC</td>\n",
       "      <td>43.50</td>\n",
       "      <td>12</td>\n",
       "      <td>26.70%</td>\n",
       "      <td>25%</td>\n",
       "      <td>10 mi to 50% (12 points)</td>\n",
       "      <td>28 mi to 90% (49 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Presidio Heights</td>\n",
       "      <td>SFC</td>\n",
       "      <td>6.50</td>\n",
       "      <td>1.4</td>\n",
       "      <td>21.60%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.2 mi to 25% (1.8 points)</td>\n",
       "      <td>0.2 mi to 25% (1.8 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Panhandle</td>\n",
       "      <td>SFC</td>\n",
       "      <td>7.30</td>\n",
       "      <td>1.5</td>\n",
       "      <td>20.60%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.3 mi to 25% (2.1 points)</td>\n",
       "      <td>0.3 mi to 25% (2.1 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Balboa Terrace</td>\n",
       "      <td>SFC</td>\n",
       "      <td>3.40</td>\n",
       "      <td>0.6</td>\n",
       "      <td>18.20%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.2 mi to 25% (1.1 points)</td>\n",
       "      <td>0.2 mi to 25% (1.1 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Polk Gulch</td>\n",
       "      <td>SFC</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0.7</td>\n",
       "      <td>18.20%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.3 mi to 25% (1.3 points)</td>\n",
       "      <td>0.3 mi to 25% (1.3 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Cole Valley</td>\n",
       "      <td>SFC</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.3</td>\n",
       "      <td>18.00%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.1 mi to 25% (0.5 points)</td>\n",
       "      <td>0.1 mi to 25% (0.5 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Forest Hill</td>\n",
       "      <td>SFC</td>\n",
       "      <td>6.10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.90%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.6 mi to 25% (2.1 points)</td>\n",
       "      <td>0.6 mi to 25% (2.1 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Clarendon Heights</td>\n",
       "      <td>SFC</td>\n",
       "      <td>6.00</td>\n",
       "      <td>0.9</td>\n",
       "      <td>14.20%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.6 mi to 25% (2.1 points)</td>\n",
       "      <td>0.6 mi to 25% (2.1 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sutro Heights</td>\n",
       "      <td>SFC</td>\n",
       "      <td>7.10</td>\n",
       "      <td>0.9</td>\n",
       "      <td>13.20%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.8 mi to 25% (2.6 points)</td>\n",
       "      <td>0.8 mi to 25% (2.6 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Ashbury Heights</td>\n",
       "      <td>SFC</td>\n",
       "      <td>3.70</td>\n",
       "      <td>0.5</td>\n",
       "      <td>13.00%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.4 mi to 25% (1.4 points)</td>\n",
       "      <td>0.4 mi to 25% (1.4 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Cow Hollow</td>\n",
       "      <td>SFC</td>\n",
       "      <td>12.00</td>\n",
       "      <td>1.4</td>\n",
       "      <td>11.90%</td>\n",
       "      <td>none</td>\n",
       "      <td>1.6 mi to 25% (4.6 points)</td>\n",
       "      <td>1.6 mi to 25% (4.6 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Golden Gate Heights</td>\n",
       "      <td>SFC</td>\n",
       "      <td>17.80</td>\n",
       "      <td>1.9</td>\n",
       "      <td>10.70%</td>\n",
       "      <td>none</td>\n",
       "      <td>2.5 mi to 25% (7.0 points)</td>\n",
       "      <td>2.5 mi to 25% (7.0 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Pacific Heights</td>\n",
       "      <td>SFC</td>\n",
       "      <td>18.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>10.70%</td>\n",
       "      <td>none</td>\n",
       "      <td>2.6 mi to 25% (7.1 points)</td>\n",
       "      <td>2.6 mi to 25% (7.1 points)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     name county  total done     pct badge  \\\n",
       "                 Dogpatch    SFC   5.10  3.1  61.04%   50%   \n",
       "              South Beach    SFC   5.53  3.3  59.00%   50%   \n",
       "              India Basin    SFC   6.00  3.5  57.57%   50%   \n",
       "              Rincon Hill    SFC   3.49  1.6  46.83%   25%   \n",
       "         Presidio Terrace    SFC   2.80  1.2  43.90%   25%   \n",
       "        Fisherman's Wharf    SFC   6.27  2.7  43.20%   25%   \n",
       "      Northern Waterfront    SFC   6.15  2.6  41.48%   25%   \n",
       "             Lincoln Park    SFC   4.50  1.8  39.60%   25%   \n",
       "              Lake Street    SFC   3.90  1.4  36.80%   25%   \n",
       "       Central Waterfront    SFC  11.67  4.2  35.99%   25%   \n",
       "            Hunters Point    SFC   8.35  3.0  35.38%   25%   \n",
       "    Candkestick Point Sra    SFC  12.39  4.2  34.10%   25%   \n",
       "  Aquatic Park Fort Mason    SFC   4.41  1.5  34.04%   25%   \n",
       "         Little Hollywood    SFC   3.70  1.1  30.74%   25%   \n",
       "       Financial District    SFC  11.43  3.5  30.57%   25%   \n",
       "               Bret Harte    SFC   9.03  2.8  30.49%   25%   \n",
       "                  Bayview    SFC  25.63  7.8  30.44%   25%   \n",
       "              Mission Bay    SFC  16.00  4.8  30.00%   25%   \n",
       "         Golden Gate Park    SFC  40.80   12  29.40%   25%   \n",
       "                 Seacliff    SFC   4.10  1.2  29.30%   25%   \n",
       "   Presidio National Park    SFC  43.50   12  26.70%   25%   \n",
       "         Presidio Heights    SFC   6.50  1.4  21.60%  none   \n",
       "                Panhandle    SFC   7.30  1.5  20.60%  none   \n",
       "           Balboa Terrace    SFC   3.40  0.6  18.20%  none   \n",
       "               Polk Gulch    SFC   4.00  0.7  18.20%  none   \n",
       "              Cole Valley    SFC   1.70  0.3  18.00%  none   \n",
       "              Forest Hill    SFC   6.10  1.0  15.90%  none   \n",
       "        Clarendon Heights    SFC   6.00  0.9  14.20%  none   \n",
       "            Sutro Heights    SFC   7.10  0.9  13.20%  none   \n",
       "          Ashbury Heights    SFC   3.70  0.5  13.00%  none   \n",
       "               Cow Hollow    SFC  12.00  1.4  11.90%  none   \n",
       "      Golden Gate Heights    SFC  17.80  1.9  10.70%  none   \n",
       "          Pacific Heights    SFC  18.00  1.9  10.70%  none   \n",
       "\n",
       "                 to next badge                  to big badge  \n",
       "    0.7 mi to 75% (1.2 points)    1.5 mi to 90% (4.0 points)  \n",
       "    0.9 mi to 75% (1.4 points)    1.7 mi to 90% (4.5 points)  \n",
       "    1.0 mi to 75% (1.6 points)    1.9 mi to 90% (4.9 points)  \n",
       "    0.1 mi to 50% (0.3 points)    1.5 mi to 90% (3.3 points)  \n",
       "    0.2 mi to 50% (0.3 points)    1.3 mi to 90% (2.7 points)  \n",
       "    0.4 mi to 50% (0.7 points)    2.9 mi to 90% (6.1 points)  \n",
       "    0.5 mi to 50% (0.8 points)    3.0 mi to 90% (6.1 points)  \n",
       "    0.5 mi to 50% (0.7 points)    2.3 mi to 90% (4.5 points)  \n",
       "    0.5 mi to 50% (0.7 points)    2.1 mi to 90% (4.0 points)  \n",
       "    1.6 mi to 50% (2.2 points)     6.3 mi to 90% (12 points)  \n",
       "    1.2 mi to 50% (1.6 points)    4.6 mi to 90% (8.7 points)  \n",
       "    2.0 mi to 50% (2.6 points)     6.9 mi to 90% (13 points)  \n",
       "    0.7 mi to 50% (0.9 points)    2.5 mi to 90% (4.7 points)  \n",
       "    0.7 mi to 50% (0.9 points)    2.2 mi to 90% (4.0 points)  \n",
       "    2.2 mi to 50% (2.8 points)     6.8 mi to 90% (13 points)  \n",
       "    1.8 mi to 50% (2.2 points)    5.4 mi to 90% (9.9 points)  \n",
       "    5.0 mi to 50% (6.3 points)      15 mi to 90% (28 points)  \n",
       "    3.2 mi to 50% (4.0 points)     9.6 mi to 90% (18 points)  \n",
       "     8.4 mi to 50% (10 points)      25 mi to 90% (45 points)  \n",
       "    0.8 mi to 50% (1.1 points)    2.5 mi to 90% (4.5 points)  \n",
       "      10 mi to 50% (12 points)      28 mi to 90% (49 points)  \n",
       "    0.2 mi to 25% (1.8 points)    0.2 mi to 25% (1.8 points)  \n",
       "    0.3 mi to 25% (2.1 points)    0.3 mi to 25% (2.1 points)  \n",
       "    0.2 mi to 25% (1.1 points)    0.2 mi to 25% (1.1 points)  \n",
       "    0.3 mi to 25% (1.3 points)    0.3 mi to 25% (1.3 points)  \n",
       "    0.1 mi to 25% (0.5 points)    0.1 mi to 25% (0.5 points)  \n",
       "    0.6 mi to 25% (2.1 points)    0.6 mi to 25% (2.1 points)  \n",
       "    0.6 mi to 25% (2.1 points)    0.6 mi to 25% (2.1 points)  \n",
       "    0.8 mi to 25% (2.6 points)    0.8 mi to 25% (2.6 points)  \n",
       "    0.4 mi to 25% (1.4 points)    0.4 mi to 25% (1.4 points)  \n",
       "    1.6 mi to 25% (4.6 points)    1.6 mi to 25% (4.6 points)  \n",
       "    2.5 mi to 25% (7.0 points)    2.5 mi to 25% (7.0 points)  \n",
       "    2.6 mi to 25% (7.1 points)    2.6 mi to 25% (7.1 points)  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wandrer(county='SFC')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wandering: Other Places"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>county</th>\n",
       "      <th>total</th>\n",
       "      <th>done</th>\n",
       "      <th>pct</th>\n",
       "      <th>badge</th>\n",
       "      <th>to next badge</th>\n",
       "      <th>to big badge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Rosie Riveter Park</td>\n",
       "      <td>CCC</td>\n",
       "      <td>5.50</td>\n",
       "      <td>4.0</td>\n",
       "      <td>73.20%</td>\n",
       "      <td>50%</td>\n",
       "      <td>0.1 mi to 75% (0.6 points)</td>\n",
       "      <td>0.9 mi to 90% (3.7 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Barangaroo</td>\n",
       "      <td>NSW</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.8</td>\n",
       "      <td>47.30%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.0 mi to 50% (0.1 points)</td>\n",
       "      <td>0.7 mi to 90% (1.6 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mt Tamalpais State Park</td>\n",
       "      <td>MAR</td>\n",
       "      <td>31.70</td>\n",
       "      <td>12</td>\n",
       "      <td>38.46%</td>\n",
       "      <td>25%</td>\n",
       "      <td>3.7 mi to 50% (5.2 points)</td>\n",
       "      <td>16 mi to 90% (32 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Muir Beach</td>\n",
       "      <td>MAR</td>\n",
       "      <td>4.60</td>\n",
       "      <td>1.7</td>\n",
       "      <td>37.10%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.6 mi to 50% (0.8 points)</td>\n",
       "      <td>2.4 mi to 90% (4.7 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>MIT</td>\n",
       "      <td>MAS</td>\n",
       "      <td>9.60</td>\n",
       "      <td>3.3</td>\n",
       "      <td>34.70%</td>\n",
       "      <td>25%</td>\n",
       "      <td>1.5 mi to 50% (1.9 points)</td>\n",
       "      <td>5.3 mi to 90% (10 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Millers Point</td>\n",
       "      <td>NSW</td>\n",
       "      <td>3.20</td>\n",
       "      <td>1.1</td>\n",
       "      <td>34.30%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.5 mi to 50% (0.7 points)</td>\n",
       "      <td>1.8 mi to 90% (3.4 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Stinson Beach</td>\n",
       "      <td>MAR</td>\n",
       "      <td>11.20</td>\n",
       "      <td>3.7</td>\n",
       "      <td>32.90%</td>\n",
       "      <td>25%</td>\n",
       "      <td>1.9 mi to 50% (2.5 points)</td>\n",
       "      <td>6.4 mi to 90% (12 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Marin Headlands GGNRA</td>\n",
       "      <td>MAR</td>\n",
       "      <td>65.70</td>\n",
       "      <td>21</td>\n",
       "      <td>31.90%</td>\n",
       "      <td>25%</td>\n",
       "      <td>12 mi to 50% (15 points)</td>\n",
       "      <td>38 mi to 90% (71 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Dawes Point</td>\n",
       "      <td>NSW</td>\n",
       "      <td>1.80</td>\n",
       "      <td>0.5</td>\n",
       "      <td>29.20%</td>\n",
       "      <td>25%</td>\n",
       "      <td>0.4 mi to 50% (0.5 points)</td>\n",
       "      <td>1.1 mi to 90% (2.0 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sausalito</td>\n",
       "      <td>MAR</td>\n",
       "      <td>32.70</td>\n",
       "      <td>9.1</td>\n",
       "      <td>27.90%</td>\n",
       "      <td>25%</td>\n",
       "      <td>7.2 mi to 50% (8.9 points)</td>\n",
       "      <td>20 mi to 90% (37 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mokelumne Hill</td>\n",
       "      <td>CAL</td>\n",
       "      <td>14.70</td>\n",
       "      <td>3.9</td>\n",
       "      <td>26.80%</td>\n",
       "      <td>25%</td>\n",
       "      <td>3.4 mi to 50% (4.1 points)</td>\n",
       "      <td>9.3 mi to 90% (17 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Guerneville</td>\n",
       "      <td>SON</td>\n",
       "      <td>22.70</td>\n",
       "      <td>5.5</td>\n",
       "      <td>24.08%</td>\n",
       "      <td>none</td>\n",
       "      <td>0.2 mi to 25% (5.9 points)</td>\n",
       "      <td>0.2 mi to 25% (5.9 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mt Tamalpais Watershed</td>\n",
       "      <td>MAR</td>\n",
       "      <td>102.87</td>\n",
       "      <td>23</td>\n",
       "      <td>22.55%</td>\n",
       "      <td>none</td>\n",
       "      <td>2.5 mi to 25% (28 points)</td>\n",
       "      <td>2.5 mi to 25% (28 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Bodega Bay</td>\n",
       "      <td>SON</td>\n",
       "      <td>28.90</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17.23%</td>\n",
       "      <td>none</td>\n",
       "      <td>2.2 mi to 25% (9.5 points)</td>\n",
       "      <td>2.2 mi to 25% (9.5 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mill Valley</td>\n",
       "      <td>MAR</td>\n",
       "      <td>92.20</td>\n",
       "      <td>12</td>\n",
       "      <td>13.43%</td>\n",
       "      <td>none</td>\n",
       "      <td>11 mi to 25% (34 points)</td>\n",
       "      <td>11 mi to 25% (34 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Corte Madera</td>\n",
       "      <td>MAR</td>\n",
       "      <td>51.00</td>\n",
       "      <td>6.6</td>\n",
       "      <td>12.90%</td>\n",
       "      <td>none</td>\n",
       "      <td>6.2 mi to 25% (19 points)</td>\n",
       "      <td>6.2 mi to 25% (19 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Healdsburg</td>\n",
       "      <td>SON</td>\n",
       "      <td>56.59</td>\n",
       "      <td>3.6</td>\n",
       "      <td>6.42%</td>\n",
       "      <td>none</td>\n",
       "      <td>11 mi to 25% (25 points)</td>\n",
       "      <td>11 mi to 25% (25 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Cambridge</td>\n",
       "      <td>MAS</td>\n",
       "      <td>180.80</td>\n",
       "      <td>11</td>\n",
       "      <td>6.20%</td>\n",
       "      <td>none</td>\n",
       "      <td>34 mi to 25% (79 points)</td>\n",
       "      <td>34 mi to 25% (79 points)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>San Rafael</td>\n",
       "      <td>MAR</td>\n",
       "      <td>260.00</td>\n",
       "      <td>9.6</td>\n",
       "      <td>3.70%</td>\n",
       "      <td>none</td>\n",
       "      <td>55 mi to 25% (120 points)</td>\n",
       "      <td>55 mi to 25% (120 points)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     name county   total done     pct badge  \\\n",
       "       Rosie Riveter Park    CCC    5.50  4.0  73.20%   50%   \n",
       "               Barangaroo    NSW    1.70  0.8  47.30%   25%   \n",
       "  Mt Tamalpais State Park    MAR   31.70   12  38.46%   25%   \n",
       "               Muir Beach    MAR    4.60  1.7  37.10%   25%   \n",
       "                      MIT    MAS    9.60  3.3  34.70%   25%   \n",
       "            Millers Point    NSW    3.20  1.1  34.30%   25%   \n",
       "            Stinson Beach    MAR   11.20  3.7  32.90%   25%   \n",
       "    Marin Headlands GGNRA    MAR   65.70   21  31.90%   25%   \n",
       "              Dawes Point    NSW    1.80  0.5  29.20%   25%   \n",
       "                Sausalito    MAR   32.70  9.1  27.90%   25%   \n",
       "           Mokelumne Hill    CAL   14.70  3.9  26.80%   25%   \n",
       "              Guerneville    SON   22.70  5.5  24.08%  none   \n",
       "   Mt Tamalpais Watershed    MAR  102.87   23  22.55%  none   \n",
       "               Bodega Bay    SON   28.90  5.0  17.23%  none   \n",
       "              Mill Valley    MAR   92.20   12  13.43%  none   \n",
       "             Corte Madera    MAR   51.00  6.6  12.90%  none   \n",
       "               Healdsburg    SON   56.59  3.6   6.42%  none   \n",
       "                Cambridge    MAS  180.80   11   6.20%  none   \n",
       "               San Rafael    MAR  260.00  9.6   3.70%  none   \n",
       "\n",
       "                 to next badge                  to big badge  \n",
       "    0.1 mi to 75% (0.6 points)    0.9 mi to 90% (3.7 points)  \n",
       "    0.0 mi to 50% (0.1 points)    0.7 mi to 90% (1.6 points)  \n",
       "    3.7 mi to 50% (5.2 points)      16 mi to 90% (32 points)  \n",
       "    0.6 mi to 50% (0.8 points)    2.4 mi to 90% (4.7 points)  \n",
       "    1.5 mi to 50% (1.9 points)     5.3 mi to 90% (10 points)  \n",
       "    0.5 mi to 50% (0.7 points)    1.8 mi to 90% (3.4 points)  \n",
       "    1.9 mi to 50% (2.5 points)     6.4 mi to 90% (12 points)  \n",
       "      12 mi to 50% (15 points)      38 mi to 90% (71 points)  \n",
       "    0.4 mi to 50% (0.5 points)    1.1 mi to 90% (2.0 points)  \n",
       "    7.2 mi to 50% (8.9 points)      20 mi to 90% (37 points)  \n",
       "    3.4 mi to 50% (4.1 points)     9.3 mi to 90% (17 points)  \n",
       "    0.2 mi to 25% (5.9 points)    0.2 mi to 25% (5.9 points)  \n",
       "     2.5 mi to 25% (28 points)     2.5 mi to 25% (28 points)  \n",
       "    2.2 mi to 25% (9.5 points)    2.2 mi to 25% (9.5 points)  \n",
       "      11 mi to 25% (34 points)      11 mi to 25% (34 points)  \n",
       "     6.2 mi to 25% (19 points)     6.2 mi to 25% (19 points)  \n",
       "      11 mi to 25% (25 points)      11 mi to 25% (25 points)  \n",
       "      34 mi to 25% (79 points)      34 mi to 25% (79 points)  \n",
       "     55 mi to 25% (120 points)     55 mi to 25% (120 points)  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wandrer(other_places)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As part of my wandering, in April 2022 I was able to get to 25% of every city that  rings the San Francisco Bay and is below San Francisco or  Oakland (see map [with](ring2.jpeg) or [without](ring1.jpeg) roads traveled; as soon as you get 25% of a city, it lights up with a color).\n",
    "\n",
    "## Leaders in Santa Clara and San Mateo Counties\n",
    "\n",
    "I live at the border of  San Mateo County (SMC) and Santa Clara County (SCC), so I ride in both, as do several other Wandrers.  Megan Gardner is 600 miles ahead of me in SMC and Jason Molenda is a whopping 1,300 miles ahead of me in SCC. Megan is the leader in mean percent between the two counties, but I lead in total miles and in geometric mean percent. Kudos to all of the riders below, who are the wandrer.earth leaders in these two counties."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>SMC %</th>\n",
       "      <th>SCC %</th>\n",
       "      <th>SMC miles</th>\n",
       "      <th>SCC miles</th>\n",
       "      <th>Total miles</th>\n",
       "      <th>GeoMean %</th>\n",
       "      <th>Mean %</th>\n",
       "      <th>Initials</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Megan Gardner</td>\n",
       "      <td>99.94</td>\n",
       "      <td>25.21</td>\n",
       "      <td>2826</td>\n",
       "      <td>1938</td>\n",
       "      <td>4764</td>\n",
       "      <td>50.19</td>\n",
       "      <td>62.58</td>\n",
       "      <td>MG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Peter Norvig</td>\n",
       "      <td>78.80</td>\n",
       "      <td>38.83</td>\n",
       "      <td>2228</td>\n",
       "      <td>2986</td>\n",
       "      <td>5214</td>\n",
       "      <td>55.32</td>\n",
       "      <td>58.81</td>\n",
       "      <td>PN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Barry Mann</td>\n",
       "      <td>78.27</td>\n",
       "      <td>31.09</td>\n",
       "      <td>2213</td>\n",
       "      <td>2390</td>\n",
       "      <td>4603</td>\n",
       "      <td>49.33</td>\n",
       "      <td>54.68</td>\n",
       "      <td>BM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Matthew Ring</td>\n",
       "      <td>83.16</td>\n",
       "      <td>2.48</td>\n",
       "      <td>2351</td>\n",
       "      <td>191</td>\n",
       "      <td>2542</td>\n",
       "      <td>14.36</td>\n",
       "      <td>42.82</td>\n",
       "      <td>MR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Brian Feinberg</td>\n",
       "      <td>36.76</td>\n",
       "      <td>48.22</td>\n",
       "      <td>1039</td>\n",
       "      <td>3707</td>\n",
       "      <td>4746</td>\n",
       "      <td>42.10</td>\n",
       "      <td>42.49</td>\n",
       "      <td>BF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Chris Okeefe</td>\n",
       "      <td>32.17</td>\n",
       "      <td>48.30</td>\n",
       "      <td>910</td>\n",
       "      <td>3714</td>\n",
       "      <td>4624</td>\n",
       "      <td>39.42</td>\n",
       "      <td>40.23</td>\n",
       "      <td>CO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Greogory P. Smith</td>\n",
       "      <td>51.37</td>\n",
       "      <td>23.27</td>\n",
       "      <td>1452</td>\n",
       "      <td>1789</td>\n",
       "      <td>3241</td>\n",
       "      <td>34.57</td>\n",
       "      <td>37.32</td>\n",
       "      <td>GS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Catherine Kircos</td>\n",
       "      <td>54.47</td>\n",
       "      <td>16.04</td>\n",
       "      <td>1540</td>\n",
       "      <td>1233</td>\n",
       "      <td>2773</td>\n",
       "      <td>29.56</td>\n",
       "      <td>35.25</td>\n",
       "      <td>CK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Jason Molenda</td>\n",
       "      <td>7.60</td>\n",
       "      <td>56.15</td>\n",
       "      <td>215</td>\n",
       "      <td>4317</td>\n",
       "      <td>4532</td>\n",
       "      <td>20.66</td>\n",
       "      <td>31.88</td>\n",
       "      <td>JM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Jim Brooks</td>\n",
       "      <td>6.17</td>\n",
       "      <td>53.51</td>\n",
       "      <td>174</td>\n",
       "      <td>4114</td>\n",
       "      <td>4288</td>\n",
       "      <td>18.17</td>\n",
       "      <td>29.84</td>\n",
       "      <td>JB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Elliot Hoff</td>\n",
       "      <td>52.89</td>\n",
       "      <td>6.13</td>\n",
       "      <td>1495</td>\n",
       "      <td>471</td>\n",
       "      <td>1966</td>\n",
       "      <td>18.01</td>\n",
       "      <td>29.51</td>\n",
       "      <td>EH</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Name  SMC %  SCC %  SMC miles  SCC miles  Total miles  \\\n",
       "      Megan Gardner  99.94  25.21       2826       1938         4764   \n",
       "       Peter Norvig  78.80  38.83       2228       2986         5214   \n",
       "         Barry Mann  78.27  31.09       2213       2390         4603   \n",
       "       Matthew Ring  83.16   2.48       2351        191         2542   \n",
       "     Brian Feinberg  36.76  48.22       1039       3707         4746   \n",
       "       Chris Okeefe  32.17  48.30        910       3714         4624   \n",
       "  Greogory P. Smith  51.37  23.27       1452       1789         3241   \n",
       "   Catherine Kircos  54.47  16.04       1540       1233         2773   \n",
       "      Jason Molenda   7.60  56.15        215       4317         4532   \n",
       "         Jim Brooks   6.17  53.51        174       4114         4288   \n",
       "        Elliot Hoff  52.89   6.13       1495        471         1966   \n",
       "\n",
       "  GeoMean %  Mean % Initials  \n",
       "      50.19   62.58       MG  \n",
       "      55.32   58.81       PN  \n",
       "      49.33   54.68       BM  \n",
       "      14.36   42.82       MR  \n",
       "      42.10   42.49       BF  \n",
       "      39.42   40.23       CO  \n",
       "      34.57   37.32       GS  \n",
       "      29.56   35.25       CK  \n",
       "      20.66   31.88       JM  \n",
       "      18.17   29.84       JB  \n",
       "      18.01   29.51       EH  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_leaders(leaders, by='Mean %')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Eddington Number\n",
    "\n",
    "The physicist/bicyclist [Sir Arthur Eddington](https://en.wikipedia.org/wiki/Arthur_Eddington) (a contemporary of Einstein) defined the   [**Eddington Number**](https://www.triathlete.com/2011/04/training/measuring-bike-miles-eddington-number_301789) as the largest integer **E** such that you have cycled at least **E** miles on at least **E** days.\n",
    "\n",
    "My Eddington number progress over the years, in both kilometers and miles:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>Ed_km</th>\n",
       "      <th>Ed_mi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2024</td>\n",
       "      <td>104</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2023</td>\n",
       "      <td>101</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2022</td>\n",
       "      <td>96</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2021</td>\n",
       "      <td>93</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2020</td>\n",
       "      <td>87</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2019</td>\n",
       "      <td>80</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2018</td>\n",
       "      <td>77</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2017</td>\n",
       "      <td>73</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2016</td>\n",
       "      <td>67</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2015</td>\n",
       "      <td>61</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2014</td>\n",
       "      <td>46</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  year  Ed_km  Ed_mi\n",
       "  2024    104     69\n",
       "  2023    101     67\n",
       "  2022     96     66\n",
       "  2021     93     65\n",
       "  2020     87     62\n",
       "  2019     80     56\n",
       "  2018     77     54\n",
       "  2017     73     51\n",
       "  2016     67     47\n",
       "  2015     61     42\n",
       "  2014     46     35"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ed_progress(rides)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "My current Eddington Number is **104** in kilometers and **69** in miles (I've ridden at least 69 miles on at least 69 different days, but not 70 miles on 70 different days). My number is above [the median for Strava](https://swinny.net/Cycling/-4687-Calculate-your-Eddington-Number), but not nearly as good as Eddington himself: his number was **84** (in miles) when he died at age 62, and his roads, weather, bicycles, and navigation aids were not nearly as nice as mine, so hip hip and bravo zulu to him. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many more rides will I need to reach higher Eddington numbers? I call that the *Eddington Gap*:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>kms</th>\n",
       "      <th>kms gap</th>\n",
       "      <th>miles</th>\n",
       "      <th>miles gap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>105</td>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>106</td>\n",
       "      <td>5</td>\n",
       "      <td>71</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>107</td>\n",
       "      <td>13</td>\n",
       "      <td>72</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>108</td>\n",
       "      <td>17</td>\n",
       "      <td>73</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>109</td>\n",
       "      <td>23</td>\n",
       "      <td>74</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>110</td>\n",
       "      <td>31</td>\n",
       "      <td>75</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>111</td>\n",
       "      <td>39</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>112</td>\n",
       "      <td>50</td>\n",
       "      <td>77</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>113</td>\n",
       "      <td>55</td>\n",
       "      <td>78</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  kms  kms gap  miles  miles gap\n",
       "  105        1     70          9\n",
       "  106        5     71         19\n",
       "  107       13     72         24\n",
       "  108       17     73         31\n",
       "  109       23     74         35\n",
       "  110       31     75         45\n",
       "  111       39     76         48\n",
       "  112       50     77         51\n",
       "  113       55     78         56"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ed_gaps(rides)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I need 1 ride of 105 km to increase my metric Eddington number to 105 kms, and I need 9 rides of 70 miles to increase my Imperial number. \n",
    "\n",
    "A 70 mile ride is getting somewhat long for me, so I might switch from Eddington numbers to number of metric centuries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "129"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count(rides.kms >= 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are some properties of Eddington numbers:\n",
    "- Your Eddington number is monotonic: it can never decrease over time. \n",
    "- To improve from an Eddington number of *n* to *n* + 1 can take as few as 1 ride, or as many as *n* + 1 rides.\n",
    "  + *Suppose you have done 9 rides, each of exactly 10 miles. Your Eddington number is 9.*\n",
    "  + *You would need 1 ride of 10 miles to improve from a number of 9 to 10.*\n",
    "  + *You would then need 11 rides of 11 miles to improve from a number 10 to 11.*\n",
    "- Your metric Eddington number will always be greater than or equal to your imperial Eddington number.\n",
    "- Your metric Eddington number will never be more than 1.61 times your  imperial Eddington number.\n",
    "- Of two riders, it is possible that one has a higher metric number and the other a higher imperial number.\n",
    "\n",
    "**Note:** the definition of Eddington Number seems precise, but what exactly does ***day*** mean? The New Oxford dictionary has three senses:\n",
    "\n",
    "1. *a period of 24 hours;*\n",
    "2. *a unit of time, reckoned from one midnight to the next;*\n",
    "3. *the part of a day when it is light.* \n",
    "\n",
    "I originally assumed sense 2, but I wanted to accept sense 1 for what [bikepackers](https://bikepacking.com/) call a [sub-24-hour overnight](https://oneofsevenproject.com/s24o-bikepacking-guide/) (S24O): a ride to a camping site in the afternoon, pitching a tent for the night, and returning back home the next morning.  And then COVID struck, the camping sites closed, so why not allow an S24O where I sleep in my own home? I realize Eddington had a lot more hardships than we have (World War I, the 1918 pandemic, and World War II, for example), but I hope he would approve of this modest accomodation on my part."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hill-Index: Speed versus Grade on Short Climbs\n",
    "\n",
    "The Eddington number reminds me of the [**h-index**](https://en.wikipedia.org/wiki/H-index) metric for scientific publications. I invented another metric:\n",
    "\n",
    "> *Your **hill-index** is the maximum integer **h** where you can regularly climb an **h** percent grade at **h** miles per hour.*\n",
    "\n",
    "I'll plot grade versus speed for segments (not rides) with two best-fit curves: a blue quadratic and an orange cubic. I'll also superimpose a red dotted line where grade = speed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show('pct', 'mph', segments[segments.pct > 2], \n",
    "     'Miles per hour versus segment grade in percent')\n",
    "plt.plot((2, 6, 7), (2, 6, 7), 'ro:');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both  best-fit curves are above the red circle at 6% and below the red circle for 7%, so  **my hill-index is 6**. We also see that I can cruise at 14 mph on a 2% grade, but only about 7 mph at 6% grade, and around 5.5 mph on 8% grades."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " # Speed versus Grade on Long Rides\n",
    "\n",
    "The plot above tell me how fast I should expect to climb a particular hill, but what about average time on longer rides? Here's a plot of my speed versus steepness (measured in feet climbed per mile rather than in percent)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show('fpmi', 'mph', rides, 'Speed (miles per hour) versus Ride Grade (feet per mile)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, I average a little under 14 mph when the overall route is fairly flat, with a lot of variability, depending more on my level of effort (and maybe the wind) than on the grade of the road. But when the grade is steeper than 50 ft/mile, my speed falls off quickly: down to 12mph at 80 ft/mile;  11 mph at 100 ft/mile; and around 10 mph at 120 ft/mile. Note that 120 ft/mile is only 2.3% grade, but if you figure a typical route is 1/3 up, 1/3 down, and 1/3 flat, then that's 7% average grade on the up part.\n",
    "\n",
    "I can use this to predict the time of a ride.  For example, if I'm in  La Honda and want to get to Pescadero, which  way is faster: the [coast route](https://www.google.com/maps/dir/La+Honda,+California/Pescadero,+California/@37.2905834,-122.3896683,12z/data=!4m19!4m18!1m10!1m1!1s0x808faed4dc6265bd:0x51a109d3306a7219!2m2!1d-122.274227!2d37.3190255!3m4!1m2!1d-122.4039496!2d37.3116594!3s0x808f062b7d7585e7:0x942480c22f110b74!1m5!1m1!1s0x808f00b4b613c4c1:0x43c609077878b77!2m2!1d-122.3830152!2d37.2551636!3e1) (15.7 miles, 361 ft climb), or the  [creek route](https://www.google.com/maps/dir/La+Honda,+California/Pescadero,+California/@37.2905834,-122.3896683,12z/data=!4m19!4m18!1m10!1m1!1s0x808faed4dc6265bd:0x51a109d3306a7219!2m2!1d-122.274227!2d37.3190255!3m4!1m2!1d-122.3658887!2d37.2538867!3s0x808f00acf265bd43:0xb7e2a0c9ee355c3a!1m5!1m1!1s0x808f00b4b613c4c1:0x43c609077878b77!2m2!1d-122.3830152!2d37.2551636!3e1) (13.5 miles, 853 ft climb)? We can estimate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Coast: 70 min, Creek: 64 min.'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f'Coast: {estimate(15.7, 361)} min, Creek: {estimate(13.5, 853)} min.'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This predicts the shorter but steeper creek route would be about 6 minutes faster (whereas Google Maps predicts the creek route would be 80 minutes, 2 more than the coast route—I guess Google lacks confidence in my climbing ability).  This is all good to know, but other factors (like the scenery and whether I want to stop at the San Gregorio store) are probably more important in making the choice."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# VAM\n",
    "\n",
    "Climbing speed is measured by [VAM](https://en.wikipedia.org/wiki/VAM_%28bicycling%29), which stands for *velocità ascensionale media* (for native Campagnolo speakers) or *vertical ascent in meters per hour* (for SRAM) or 平均上昇率 (for Shimano), or *Vm/h* (for physicists). The theory is that for fairly steep climbs, most of your power is going into lifting against gravity, so your VAM should be about constant no matter what the grade. (For flatish segments power is spent on wind and rolling resistance, and for the very steepest of climbs, in my experience,  power goes largely to cursing *sotto voce*, as they say in Italian.) \n",
    "\n",
    "Here's a plot of my VAM versus grade over short segments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show('pct', 'vam', segments, 'VAM (vertical meters per hour) versus segment grade in percent')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Champion cyclists can do over 1800 meters/hour over a 10 km climb, and can sustain [1400 meters/hour for 7 hours](https://www.strava.com/activities/4996833865).  My VAM numbers range mostly from 400 to 800 meters/hour, and I can sustain the higher numbers for only a couple of minutes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Camaritas climb</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.10</td>\n",
       "      <td>48</td>\n",
       "      <td>10.00</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>480.0</td>\n",
       "      <td>9.09</td>\n",
       "      <td>0.16</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Paloma Climb</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.14</td>\n",
       "      <td>82</td>\n",
       "      <td>7.00</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>586.0</td>\n",
       "      <td>11.09</td>\n",
       "      <td>0.23</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Klamath Dr.</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.12</td>\n",
       "      <td>77</td>\n",
       "      <td>6.00</td>\n",
       "      <td>1173.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>12.15</td>\n",
       "      <td>0.19</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Entrance Way Hill Repeats</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.10</td>\n",
       "      <td>76</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1158.0</td>\n",
       "      <td>760.0</td>\n",
       "      <td>14.39</td>\n",
       "      <td>0.16</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Davenport Kicker</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.24</td>\n",
       "      <td>74</td>\n",
       "      <td>12.00</td>\n",
       "      <td>1128.0</td>\n",
       "      <td>308.0</td>\n",
       "      <td>5.84</td>\n",
       "      <td>0.39</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Valparaiso steep</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.18</td>\n",
       "      <td>145</td>\n",
       "      <td>4.50</td>\n",
       "      <td>1105.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>15.26</td>\n",
       "      <td>0.29</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Invernes to Firecrest Climb</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.28</td>\n",
       "      <td>143</td>\n",
       "      <td>7.00</td>\n",
       "      <td>1090.0</td>\n",
       "      <td>511.0</td>\n",
       "      <td>9.67</td>\n",
       "      <td>0.45</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kings Mountain final sprint</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.31</td>\n",
       "      <td>135</td>\n",
       "      <td>7.75</td>\n",
       "      <td>1029.0</td>\n",
       "      <td>435.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>0.50</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Limantour Spit</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.47</td>\n",
       "      <td>303</td>\n",
       "      <td>5.22</td>\n",
       "      <td>1026.0</td>\n",
       "      <td>645.0</td>\n",
       "      <td>12.21</td>\n",
       "      <td>0.76</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tunitas flattens</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.42</td>\n",
       "      <td>166</td>\n",
       "      <td>8.40</td>\n",
       "      <td>1012.0</td>\n",
       "      <td>395.0</td>\n",
       "      <td>7.49</td>\n",
       "      <td>0.68</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tunitas flattens</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.42</td>\n",
       "      <td>166</td>\n",
       "      <td>8.40</td>\n",
       "      <td>1012.0</td>\n",
       "      <td>395.0</td>\n",
       "      <td>7.49</td>\n",
       "      <td>0.68</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Cemetery Sprint</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.08</td>\n",
       "      <td>33</td>\n",
       "      <td>8.00</td>\n",
       "      <td>1006.0</td>\n",
       "      <td>412.0</td>\n",
       "      <td>7.81</td>\n",
       "      <td>0.13</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Skyline Bump at OLH</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.21</td>\n",
       "      <td>63</td>\n",
       "      <td>10.50</td>\n",
       "      <td>960.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>5.68</td>\n",
       "      <td>0.34</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Laning Bump</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.24</td>\n",
       "      <td>94</td>\n",
       "      <td>8.00</td>\n",
       "      <td>955.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>7.42</td>\n",
       "      <td>0.39</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Faught Turn</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.22</td>\n",
       "      <td>60</td>\n",
       "      <td>11.00</td>\n",
       "      <td>914.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>5.17</td>\n",
       "      <td>0.35</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Westridge 3min</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.37</td>\n",
       "      <td>240</td>\n",
       "      <td>4.62</td>\n",
       "      <td>914.0</td>\n",
       "      <td>649.0</td>\n",
       "      <td>12.29</td>\n",
       "      <td>0.60</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Valparaiso steep</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.18</td>\n",
       "      <td>145</td>\n",
       "      <td>3.60</td>\n",
       "      <td>884.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>15.26</td>\n",
       "      <td>0.29</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sharon Park steep part</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.21</td>\n",
       "      <td>86</td>\n",
       "      <td>7.00</td>\n",
       "      <td>874.0</td>\n",
       "      <td>410.0</td>\n",
       "      <td>7.76</td>\n",
       "      <td>0.34</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Old La Honda Mile 1</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.99</td>\n",
       "      <td>370</td>\n",
       "      <td>7.62</td>\n",
       "      <td>868.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>7.08</td>\n",
       "      <td>1.59</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Joaquin</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.33</td>\n",
       "      <td>254</td>\n",
       "      <td>3.67</td>\n",
       "      <td>860.0</td>\n",
       "      <td>770.0</td>\n",
       "      <td>14.58</td>\n",
       "      <td>0.53</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        title  hours  miles  feet    mph     vam   fpmi  \\\n",
       "              Camaritas climb   0.01   0.10    48  10.00  1463.0  480.0   \n",
       "                 Paloma Climb   0.02   0.14    82   7.00  1250.0  586.0   \n",
       "                  Klamath Dr.   0.02   0.12    77   6.00  1173.0  642.0   \n",
       "    Entrance Way Hill Repeats   0.02   0.10    76   5.00  1158.0  760.0   \n",
       "             Davenport Kicker   0.02   0.24    74  12.00  1128.0  308.0   \n",
       "             Valparaiso steep   0.04   0.18   145   4.50  1105.0  806.0   \n",
       "  Invernes to Firecrest Climb   0.04   0.28   143   7.00  1090.0  511.0   \n",
       "  Kings Mountain final sprint   0.04   0.31   135   7.75  1029.0  435.0   \n",
       "               Limantour Spit   0.09   0.47   303   5.22  1026.0  645.0   \n",
       "             Tunitas flattens   0.05   0.42   166   8.40  1012.0  395.0   \n",
       "             Tunitas flattens   0.05   0.42   166   8.40  1012.0  395.0   \n",
       "              Cemetery Sprint   0.01   0.08    33   8.00  1006.0  412.0   \n",
       "          Skyline Bump at OLH   0.02   0.21    63  10.50   960.0  300.0   \n",
       "                  Laning Bump   0.03   0.24    94   8.00   955.0  392.0   \n",
       "                  Faught Turn   0.02   0.22    60  11.00   914.0  273.0   \n",
       "               Westridge 3min   0.08   0.37   240   4.62   914.0  649.0   \n",
       "             Valparaiso steep   0.05   0.18   145   3.60   884.0  806.0   \n",
       "       Sharon Park steep part   0.03   0.21    86   7.00   874.0  410.0   \n",
       "          Old La Honda Mile 1   0.13   0.99   370   7.62   868.0  374.0   \n",
       "                      Joaquin   0.09   0.33   254   3.67   860.0  770.0   \n",
       "\n",
       "    pct   kms  meters  \n",
       "   9.09  0.16    15.0  \n",
       "  11.09  0.23    25.0  \n",
       "  12.15  0.19    23.0  \n",
       "  14.39  0.16    23.0  \n",
       "   5.84  0.39    23.0  \n",
       "  15.26  0.29    44.0  \n",
       "   9.67  0.45    44.0  \n",
       "   8.25  0.50    41.0  \n",
       "  12.21  0.76    92.0  \n",
       "   7.49  0.68    51.0  \n",
       "   7.49  0.68    51.0  \n",
       "   7.81  0.13    10.0  \n",
       "   5.68  0.34    19.0  \n",
       "   7.42  0.39    29.0  \n",
       "   5.17  0.35    18.0  \n",
       "  12.29  0.60    73.0  \n",
       "  15.26  0.29    44.0  \n",
       "   7.76  0.34    26.0  \n",
       "   7.08  1.59   113.0  \n",
       "  14.58  0.53    77.0  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments, 'vam')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On segments that are at least a kilometer long my VAM tops out at about 800 meters/hour:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Old La Honda Mile 1</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.99</td>\n",
       "      <td>370</td>\n",
       "      <td>7.62</td>\n",
       "      <td>868.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>7.08</td>\n",
       "      <td>1.59</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Westridge</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.68</td>\n",
       "      <td>385</td>\n",
       "      <td>4.86</td>\n",
       "      <td>838.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>10.72</td>\n",
       "      <td>1.09</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Old La Honda (Bridge to Stop)</td>\n",
       "      <td>0.48</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1255</td>\n",
       "      <td>6.94</td>\n",
       "      <td>797.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>7.14</td>\n",
       "      <td>5.36</td>\n",
       "      <td>383.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Old La Honda (Bridge to Stop)</td>\n",
       "      <td>0.51</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1255</td>\n",
       "      <td>6.53</td>\n",
       "      <td>750.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>7.14</td>\n",
       "      <td>5.36</td>\n",
       "      <td>383.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Westridge</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.68</td>\n",
       "      <td>385</td>\n",
       "      <td>4.25</td>\n",
       "      <td>733.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>10.72</td>\n",
       "      <td>1.09</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tunitas steep</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.20</td>\n",
       "      <td>599</td>\n",
       "      <td>4.80</td>\n",
       "      <td>730.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>9.45</td>\n",
       "      <td>1.93</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Old La Honda Mile 1</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.99</td>\n",
       "      <td>370</td>\n",
       "      <td>6.19</td>\n",
       "      <td>705.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>7.08</td>\n",
       "      <td>1.59</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Woodside Climb</td>\n",
       "      <td>0.13</td>\n",
       "      <td>1.71</td>\n",
       "      <td>295</td>\n",
       "      <td>13.15</td>\n",
       "      <td>692.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>3.27</td>\n",
       "      <td>2.75</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Huddart</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.92</td>\n",
       "      <td>385</td>\n",
       "      <td>5.41</td>\n",
       "      <td>690.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1.48</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Top of Groton Rd heading west</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.92</td>\n",
       "      <td>291</td>\n",
       "      <td>7.08</td>\n",
       "      <td>682.0</td>\n",
       "      <td>316.0</td>\n",
       "      <td>5.99</td>\n",
       "      <td>1.48</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Watts (Sonoma)</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.20</td>\n",
       "      <td>313</td>\n",
       "      <td>8.57</td>\n",
       "      <td>681.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>4.94</td>\n",
       "      <td>1.93</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tunitas steep</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.20</td>\n",
       "      <td>599</td>\n",
       "      <td>4.44</td>\n",
       "      <td>676.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>9.45</td>\n",
       "      <td>1.93</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Canon to No Cycling</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.75</td>\n",
       "      <td>198</td>\n",
       "      <td>8.33</td>\n",
       "      <td>671.0</td>\n",
       "      <td>264.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.21</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Canon to No Cycling</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.75</td>\n",
       "      <td>198</td>\n",
       "      <td>8.33</td>\n",
       "      <td>671.0</td>\n",
       "      <td>264.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.21</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Coe Second Switchback to flat</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.00</td>\n",
       "      <td>483</td>\n",
       "      <td>4.55</td>\n",
       "      <td>669.0</td>\n",
       "      <td>483.0</td>\n",
       "      <td>9.15</td>\n",
       "      <td>1.61</td>\n",
       "      <td>147.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Lower Redwood Gulch</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.03</td>\n",
       "      <td>474</td>\n",
       "      <td>4.68</td>\n",
       "      <td>657.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>8.72</td>\n",
       "      <td>1.66</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Lobitas Creek</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.96</td>\n",
       "      <td>430</td>\n",
       "      <td>4.80</td>\n",
       "      <td>655.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>8.48</td>\n",
       "      <td>1.54</td>\n",
       "      <td>131.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>West Alpine switchback</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.78</td>\n",
       "      <td>322</td>\n",
       "      <td>5.20</td>\n",
       "      <td>654.0</td>\n",
       "      <td>413.0</td>\n",
       "      <td>7.82</td>\n",
       "      <td>1.26</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kaboom Portola Rd</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.67</td>\n",
       "      <td>102</td>\n",
       "      <td>13.40</td>\n",
       "      <td>622.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>2.88</td>\n",
       "      <td>1.08</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Huddart</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.92</td>\n",
       "      <td>385</td>\n",
       "      <td>4.84</td>\n",
       "      <td>618.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1.48</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kings Greer to Skyline</td>\n",
       "      <td>0.78</td>\n",
       "      <td>3.92</td>\n",
       "      <td>1536</td>\n",
       "      <td>5.03</td>\n",
       "      <td>600.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>7.42</td>\n",
       "      <td>6.31</td>\n",
       "      <td>468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Woodside Climb</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1.71</td>\n",
       "      <td>295</td>\n",
       "      <td>11.40</td>\n",
       "      <td>599.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>3.27</td>\n",
       "      <td>2.75</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Stage Rd</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.01</td>\n",
       "      <td>373</td>\n",
       "      <td>5.32</td>\n",
       "      <td>598.0</td>\n",
       "      <td>369.0</td>\n",
       "      <td>6.99</td>\n",
       "      <td>1.63</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Try not to fall back</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.71</td>\n",
       "      <td>410</td>\n",
       "      <td>3.38</td>\n",
       "      <td>595.0</td>\n",
       "      <td>577.0</td>\n",
       "      <td>10.94</td>\n",
       "      <td>1.14</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sand Gill Sharon-top</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.85</td>\n",
       "      <td>136</td>\n",
       "      <td>12.14</td>\n",
       "      <td>592.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>3.03</td>\n",
       "      <td>1.37</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sand Gill Sharon-top</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.85</td>\n",
       "      <td>136</td>\n",
       "      <td>12.14</td>\n",
       "      <td>592.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>3.03</td>\n",
       "      <td>1.37</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mt Eden climb</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.02</td>\n",
       "      <td>272</td>\n",
       "      <td>7.29</td>\n",
       "      <td>592.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>5.05</td>\n",
       "      <td>1.64</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tunitas lower climb</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.30</td>\n",
       "      <td>421</td>\n",
       "      <td>5.91</td>\n",
       "      <td>583.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>6.13</td>\n",
       "      <td>2.09</td>\n",
       "      <td>128.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kings Greer to Skyline</td>\n",
       "      <td>0.81</td>\n",
       "      <td>3.92</td>\n",
       "      <td>1536</td>\n",
       "      <td>4.84</td>\n",
       "      <td>578.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>7.42</td>\n",
       "      <td>6.31</td>\n",
       "      <td>468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Haskins</td>\n",
       "      <td>0.30</td>\n",
       "      <td>1.51</td>\n",
       "      <td>566</td>\n",
       "      <td>5.03</td>\n",
       "      <td>575.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>7.10</td>\n",
       "      <td>2.43</td>\n",
       "      <td>173.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          title  hours  miles  feet    mph    vam   fpmi  \\\n",
       "            Old La Honda Mile 1   0.13   0.99   370   7.62  868.0  374.0   \n",
       "                      Westridge   0.14   0.68   385   4.86  838.0  566.0   \n",
       "  Old La Honda (Bridge to Stop)   0.48   3.33  1255   6.94  797.0  377.0   \n",
       "  Old La Honda (Bridge to Stop)   0.51   3.33  1255   6.53  750.0  377.0   \n",
       "                      Westridge   0.16   0.68   385   4.25  733.0  566.0   \n",
       "                  Tunitas steep   0.25   1.20   599   4.80  730.0  499.0   \n",
       "            Old La Honda Mile 1   0.16   0.99   370   6.19  705.0  374.0   \n",
       "                 Woodside Climb   0.13   1.71   295  13.15  692.0  173.0   \n",
       "                        Huddart   0.17   0.92   385   5.41  690.0  418.0   \n",
       "  Top of Groton Rd heading west   0.13   0.92   291   7.08  682.0  316.0   \n",
       "                 Watts (Sonoma)   0.14   1.20   313   8.57  681.0  261.0   \n",
       "                  Tunitas steep   0.27   1.20   599   4.44  676.0  499.0   \n",
       "            Canon to No Cycling   0.09   0.75   198   8.33  671.0  264.0   \n",
       "            Canon to No Cycling   0.09   0.75   198   8.33  671.0  264.0   \n",
       "  Coe Second Switchback to flat   0.22   1.00   483   4.55  669.0  483.0   \n",
       "            Lower Redwood Gulch   0.22   1.03   474   4.68  657.0  460.0   \n",
       "                  Lobitas Creek   0.20   0.96   430   4.80  655.0  448.0   \n",
       "         West Alpine switchback   0.15   0.78   322   5.20  654.0  413.0   \n",
       "              Kaboom Portola Rd   0.05   0.67   102  13.40  622.0  152.0   \n",
       "                        Huddart   0.19   0.92   385   4.84  618.0  418.0   \n",
       "         Kings Greer to Skyline   0.78   3.92  1536   5.03  600.0  392.0   \n",
       "                 Woodside Climb   0.15   1.71   295  11.40  599.0  173.0   \n",
       "                       Stage Rd   0.19   1.01   373   5.32  598.0  369.0   \n",
       "           Try not to fall back   0.21   0.71   410   3.38  595.0  577.0   \n",
       "           Sand Gill Sharon-top   0.07   0.85   136  12.14  592.0  160.0   \n",
       "           Sand Gill Sharon-top   0.07   0.85   136  12.14  592.0  160.0   \n",
       "                  Mt Eden climb   0.14   1.02   272   7.29  592.0  267.0   \n",
       "            Tunitas lower climb   0.22   1.30   421   5.91  583.0  324.0   \n",
       "         Kings Greer to Skyline   0.81   3.92  1536   4.84  578.0  392.0   \n",
       "                        Haskins   0.30   1.51   566   5.03  575.0  375.0   \n",
       "\n",
       "    pct   kms  meters  \n",
       "   7.08  1.59   113.0  \n",
       "  10.72  1.09   117.0  \n",
       "   7.14  5.36   383.0  \n",
       "   7.14  5.36   383.0  \n",
       "  10.72  1.09   117.0  \n",
       "   9.45  1.93   183.0  \n",
       "   7.08  1.59   113.0  \n",
       "   3.27  2.75    90.0  \n",
       "   7.93  1.48   117.0  \n",
       "   5.99  1.48    89.0  \n",
       "   4.94  1.93    95.0  \n",
       "   9.45  1.93   183.0  \n",
       "   5.00  1.21    60.0  \n",
       "   5.00  1.21    60.0  \n",
       "   9.15  1.61   147.0  \n",
       "   8.72  1.66   144.0  \n",
       "   8.48  1.54   131.0  \n",
       "   7.82  1.26    98.0  \n",
       "   2.88  1.08    31.0  \n",
       "   7.93  1.48   117.0  \n",
       "   7.42  6.31   468.0  \n",
       "   3.27  2.75    90.0  \n",
       "   6.99  1.63   114.0  \n",
       "  10.94  1.14   125.0  \n",
       "   3.03  1.37    41.0  \n",
       "   3.03  1.37    41.0  \n",
       "   5.05  1.64    83.0  \n",
       "   6.13  2.09   128.0  \n",
       "   7.42  6.31   468.0  \n",
       "   7.10  2.43   173.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments[segments.kms >= 1], 'vam', n=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I can also look at VAM numbers for complete rides. I would expect the ride VAM to be half the segment VAM (or less) since most of my rides are circuits where I return to the start, and thus no more than half the ride is climbing. Sure enough, the best I can do is about 400 meters/hour:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 11/29/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Mt. Hamilton</td>\n",
       "      <td>3.68</td>\n",
       "      <td>37.00</td>\n",
       "      <td>4902</td>\n",
       "      <td>10.05</td>\n",
       "      <td>406.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>2.51</td>\n",
       "      <td>59.53</td>\n",
       "      <td>1494.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 4/2/2021</td>\n",
       "      <td>2021</td>\n",
       "      <td>Everesting 5: climb 2×(OLH + WOLH)</td>\n",
       "      <td>3.27</td>\n",
       "      <td>31.48</td>\n",
       "      <td>4344</td>\n",
       "      <td>9.63</td>\n",
       "      <td>405.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>2.61</td>\n",
       "      <td>50.65</td>\n",
       "      <td>1324.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mon, 3/29/2021</td>\n",
       "      <td>2021</td>\n",
       "      <td>Everesting 1: Mt Diablo</td>\n",
       "      <td>2.60</td>\n",
       "      <td>22.22</td>\n",
       "      <td>3406</td>\n",
       "      <td>8.55</td>\n",
       "      <td>399.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>2.90</td>\n",
       "      <td>35.75</td>\n",
       "      <td>1038.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tue, 3/30/2021</td>\n",
       "      <td>2021</td>\n",
       "      <td>Everesting 2: Kings + WOLH + OLH</td>\n",
       "      <td>3.34</td>\n",
       "      <td>35.99</td>\n",
       "      <td>4377</td>\n",
       "      <td>10.78</td>\n",
       "      <td>399.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>2.30</td>\n",
       "      <td>57.91</td>\n",
       "      <td>1334.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 12/1/2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>Mt. Hamilton</td>\n",
       "      <td>3.78</td>\n",
       "      <td>37.56</td>\n",
       "      <td>4921</td>\n",
       "      <td>9.94</td>\n",
       "      <td>397.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>2.48</td>\n",
       "      <td>60.43</td>\n",
       "      <td>1500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 11/25/2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>Mt. Hamilton</td>\n",
       "      <td>3.69</td>\n",
       "      <td>36.65</td>\n",
       "      <td>4806</td>\n",
       "      <td>9.93</td>\n",
       "      <td>397.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>2.48</td>\n",
       "      <td>58.97</td>\n",
       "      <td>1465.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 10/30/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>OLH / West Alpine</td>\n",
       "      <td>3.48</td>\n",
       "      <td>39.51</td>\n",
       "      <td>4505</td>\n",
       "      <td>11.35</td>\n",
       "      <td>395.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>2.16</td>\n",
       "      <td>63.57</td>\n",
       "      <td>1373.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 4/26/2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>OLH / Tunitas Creek</td>\n",
       "      <td>5.26</td>\n",
       "      <td>58.69</td>\n",
       "      <td>6742</td>\n",
       "      <td>11.16</td>\n",
       "      <td>391.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>94.43</td>\n",
       "      <td>2055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 4/18/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Tunitas + Lobitos Creeks</td>\n",
       "      <td>5.24</td>\n",
       "      <td>61.27</td>\n",
       "      <td>6611</td>\n",
       "      <td>11.69</td>\n",
       "      <td>385.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.04</td>\n",
       "      <td>98.58</td>\n",
       "      <td>2015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Wed, 10/14/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Half Moon Bay</td>\n",
       "      <td>6.13</td>\n",
       "      <td>72.97</td>\n",
       "      <td>7644</td>\n",
       "      <td>11.90</td>\n",
       "      <td>380.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>1.98</td>\n",
       "      <td>117.41</td>\n",
       "      <td>2330.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/4/2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>Sequoia Challenge</td>\n",
       "      <td>6.29</td>\n",
       "      <td>66.52</td>\n",
       "      <td>7520</td>\n",
       "      <td>10.58</td>\n",
       "      <td>364.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>2.14</td>\n",
       "      <td>107.03</td>\n",
       "      <td>2292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 7/25/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Palo Alto, California</td>\n",
       "      <td>4.04</td>\n",
       "      <td>43.62</td>\n",
       "      <td>4819</td>\n",
       "      <td>10.80</td>\n",
       "      <td>364.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>2.09</td>\n",
       "      <td>70.18</td>\n",
       "      <td>1469.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 10/11/2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>OLH / Tunitas</td>\n",
       "      <td>5.09</td>\n",
       "      <td>58.29</td>\n",
       "      <td>6044</td>\n",
       "      <td>11.45</td>\n",
       "      <td>362.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>1.96</td>\n",
       "      <td>93.79</td>\n",
       "      <td>1842.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 8/13/2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>Petaluma / Point Reyes</td>\n",
       "      <td>4.50</td>\n",
       "      <td>54.75</td>\n",
       "      <td>5286</td>\n",
       "      <td>12.17</td>\n",
       "      <td>358.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1.83</td>\n",
       "      <td>88.09</td>\n",
       "      <td>1611.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 8/28/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Pescadaro via OLH</td>\n",
       "      <td>5.31</td>\n",
       "      <td>66.01</td>\n",
       "      <td>6137</td>\n",
       "      <td>12.43</td>\n",
       "      <td>352.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>1.76</td>\n",
       "      <td>106.21</td>\n",
       "      <td>1871.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 4/4/2021</td>\n",
       "      <td>2021</td>\n",
       "      <td>Everesting 7: Mill Creek / Morrison Canyon</td>\n",
       "      <td>3.08</td>\n",
       "      <td>29.38</td>\n",
       "      <td>3517</td>\n",
       "      <td>9.54</td>\n",
       "      <td>348.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>2.27</td>\n",
       "      <td>47.27</td>\n",
       "      <td>1072.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 2/10/2024</td>\n",
       "      <td>2024</td>\n",
       "      <td>Seacliff, etc.</td>\n",
       "      <td>4.72</td>\n",
       "      <td>63.41</td>\n",
       "      <td>5365</td>\n",
       "      <td>13.43</td>\n",
       "      <td>346.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1.60</td>\n",
       "      <td>102.03</td>\n",
       "      <td>1635.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Wed, 6/18/2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>Sierra to the Sea Day 4</td>\n",
       "      <td>4.96</td>\n",
       "      <td>57.64</td>\n",
       "      <td>5561</td>\n",
       "      <td>11.62</td>\n",
       "      <td>342.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1.83</td>\n",
       "      <td>92.74</td>\n",
       "      <td>1695.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/3/2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>The Sequoia</td>\n",
       "      <td>5.97</td>\n",
       "      <td>64.92</td>\n",
       "      <td>6677</td>\n",
       "      <td>10.87</td>\n",
       "      <td>341.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1.95</td>\n",
       "      <td>104.46</td>\n",
       "      <td>2035.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/9/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>OLH</td>\n",
       "      <td>2.50</td>\n",
       "      <td>32.33</td>\n",
       "      <td>2788</td>\n",
       "      <td>12.93</td>\n",
       "      <td>340.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>1.63</td>\n",
       "      <td>52.02</td>\n",
       "      <td>850.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             date  year                                       title  hours  \\\n",
       "  Sun, 11/29/2015  2015                                Mt. Hamilton   3.68   \n",
       "    Fri, 4/2/2021  2021          Everesting 5: climb 2×(OLH + WOLH)   3.27   \n",
       "   Mon, 3/29/2021  2021                     Everesting 1: Mt Diablo   2.60   \n",
       "   Tue, 3/30/2021  2021            Everesting 2: Kings + WOLH + OLH   3.34   \n",
       "   Sun, 12/1/2013  2013                                Mt. Hamilton   3.78   \n",
       "  Sat, 11/25/2017  2017                                Mt. Hamilton   3.69   \n",
       "  Fri, 10/30/2015  2015                           OLH / West Alpine   3.48   \n",
       "   Sat, 4/26/2014  2014                         OLH / Tunitas Creek   5.26   \n",
       "   Sat, 4/18/2015  2015                    Tunitas + Lobitos Creeks   5.24   \n",
       "  Wed, 10/14/2015  2015                               Half Moon Bay   6.13   \n",
       "    Sun, 6/4/2017  2017                           Sequoia Challenge   6.29   \n",
       "   Sat, 7/25/2015  2015                       Palo Alto, California   4.04   \n",
       "  Sat, 10/11/2014  2014                               OLH / Tunitas   5.09   \n",
       "   Sat, 8/13/2016  2016                      Petaluma / Point Reyes   4.50   \n",
       "   Fri, 8/28/2015  2015                           Pescadaro via OLH   5.31   \n",
       "    Sun, 4/4/2021  2021  Everesting 7: Mill Creek / Morrison Canyon   3.08   \n",
       "   Sat, 2/10/2024  2024                              Seacliff, etc.   4.72   \n",
       "   Wed, 6/18/2014  2014                     Sierra to the Sea Day 4   4.96   \n",
       "    Sun, 6/3/2018  2018                                 The Sequoia   5.97   \n",
       "    Sat, 5/9/2015  2015                                         OLH   2.50   \n",
       "\n",
       "  miles  feet    mph    vam   fpmi   pct     kms  meters  \n",
       "  37.00  4902  10.05  406.0  132.0  2.51   59.53  1494.0  \n",
       "  31.48  4344   9.63  405.0  138.0  2.61   50.65  1324.0  \n",
       "  22.22  3406   8.55  399.0  153.0  2.90   35.75  1038.0  \n",
       "  35.99  4377  10.78  399.0  122.0  2.30   57.91  1334.0  \n",
       "  37.56  4921   9.94  397.0  131.0  2.48   60.43  1500.0  \n",
       "  36.65  4806   9.93  397.0  131.0  2.48   58.97  1465.0  \n",
       "  39.51  4505  11.35  395.0  114.0  2.16   63.57  1373.0  \n",
       "  58.69  6742  11.16  391.0  115.0  2.18   94.43  2055.0  \n",
       "  61.27  6611  11.69  385.0  108.0  2.04   98.58  2015.0  \n",
       "  72.97  7644  11.90  380.0  105.0  1.98  117.41  2330.0  \n",
       "  66.52  7520  10.58  364.0  113.0  2.14  107.03  2292.0  \n",
       "  43.62  4819  10.80  364.0  110.0  2.09   70.18  1469.0  \n",
       "  58.29  6044  11.45  362.0  104.0  1.96   93.79  1842.0  \n",
       "  54.75  5286  12.17  358.0   97.0  1.83   88.09  1611.0  \n",
       "  66.01  6137  12.43  352.0   93.0  1.76  106.21  1871.0  \n",
       "  29.38  3517   9.54  348.0  120.0  2.27   47.27  1072.0  \n",
       "  63.41  5365  13.43  346.0   85.0  1.60  102.03  1635.0  \n",
       "  57.64  5561  11.62  342.0   96.0  1.83   92.74  1695.0  \n",
       "  64.92  6677  10.87  341.0  103.0  1.95  104.46  2035.0  \n",
       "  32.33  2788  12.93  340.0   86.0  1.63   52.02   850.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(rides, 'vam')   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring the Data\n",
    "\n",
    "\n",
    "Some more ways to look at the data, both rides and segments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "      <td>555.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2017.165766</td>\n",
       "      <td>3.426595</td>\n",
       "      <td>43.794721</td>\n",
       "      <td>1863.387387</td>\n",
       "      <td>12.982378</td>\n",
       "      <td>158.131532</td>\n",
       "      <td>41.627027</td>\n",
       "      <td>0.788108</td>\n",
       "      <td>70.465640</td>\n",
       "      <td>567.967568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.758888</td>\n",
       "      <td>1.497428</td>\n",
       "      <td>18.033732</td>\n",
       "      <td>1525.600789</td>\n",
       "      <td>1.328193</td>\n",
       "      <td>89.835343</td>\n",
       "      <td>27.152923</td>\n",
       "      <td>0.514095</td>\n",
       "      <td>29.016345</td>\n",
       "      <td>464.998190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2012.000000</td>\n",
       "      <td>1.540000</td>\n",
       "      <td>20.960000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>8.550000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>33.720000</td>\n",
       "      <td>21.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2015.000000</td>\n",
       "      <td>2.230000</td>\n",
       "      <td>29.260000</td>\n",
       "      <td>746.500000</td>\n",
       "      <td>12.160000</td>\n",
       "      <td>81.500000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>47.080000</td>\n",
       "      <td>227.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2017.000000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>37.260000</td>\n",
       "      <td>1384.000000</td>\n",
       "      <td>13.120000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>0.690000</td>\n",
       "      <td>59.950000</td>\n",
       "      <td>422.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2018.000000</td>\n",
       "      <td>4.535000</td>\n",
       "      <td>60.025000</td>\n",
       "      <td>2434.500000</td>\n",
       "      <td>13.785000</td>\n",
       "      <td>218.500000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>1.070000</td>\n",
       "      <td>96.580000</td>\n",
       "      <td>742.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2025.000000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>102.410000</td>\n",
       "      <td>7644.000000</td>\n",
       "      <td>16.750000</td>\n",
       "      <td>406.000000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>164.780000</td>\n",
       "      <td>2330.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              year       hours       miles         feet         mph  \\\n",
       "count   555.000000  555.000000  555.000000   555.000000  555.000000   \n",
       "mean   2017.165766    3.426595   43.794721  1863.387387   12.982378   \n",
       "std       2.758888    1.497428   18.033732  1525.600789    1.328193   \n",
       "min    2012.000000    1.540000   20.960000    68.000000    8.550000   \n",
       "25%    2015.000000    2.230000   29.260000   746.500000   12.160000   \n",
       "50%    2017.000000    2.900000   37.260000  1384.000000   13.120000   \n",
       "75%    2018.000000    4.535000   60.025000  2434.500000   13.785000   \n",
       "max    2025.000000    8.140000  102.410000  7644.000000   16.750000   \n",
       "\n",
       "              vam        fpmi         pct         kms       meters  \n",
       "count  555.000000  555.000000  555.000000  555.000000   555.000000  \n",
       "mean   158.131532   41.627027    0.788108   70.465640   567.967568  \n",
       "std     89.835343   27.152923    0.514095   29.016345   464.998190  \n",
       "min     10.000000    3.000000    0.050000   33.720000    21.000000  \n",
       "25%     81.500000   20.000000    0.375000   47.080000   227.500000  \n",
       "50%    153.000000   36.000000    0.690000   59.950000   422.000000  \n",
       "75%    218.500000   56.000000    1.070000   96.580000   742.000000  \n",
       "max    406.000000  153.000000    2.900000  164.780000  2330.000000  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rides.describe() # Summary statistics for the rides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.141702</td>\n",
       "      <td>0.932979</td>\n",
       "      <td>268.978723</td>\n",
       "      <td>7.444539</td>\n",
       "      <td>641.893617</td>\n",
       "      <td>353.503546</td>\n",
       "      <td>6.694894</td>\n",
       "      <td>1.501064</td>\n",
       "      <td>81.978723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.173711</td>\n",
       "      <td>0.989832</td>\n",
       "      <td>295.060659</td>\n",
       "      <td>3.557336</td>\n",
       "      <td>211.923595</td>\n",
       "      <td>186.816320</td>\n",
       "      <td>3.537974</td>\n",
       "      <td>1.592267</td>\n",
       "      <td>89.957408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>2.120000</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.350000</td>\n",
       "      <td>0.130000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.330000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>4.830000</td>\n",
       "      <td>503.000000</td>\n",
       "      <td>219.000000</td>\n",
       "      <td>4.140000</td>\n",
       "      <td>0.530000</td>\n",
       "      <td>32.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>6.190000</td>\n",
       "      <td>630.000000</td>\n",
       "      <td>333.000000</td>\n",
       "      <td>6.300000</td>\n",
       "      <td>0.970000</td>\n",
       "      <td>51.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.150000</td>\n",
       "      <td>1.190000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>9.800000</td>\n",
       "      <td>724.000000</td>\n",
       "      <td>462.000000</td>\n",
       "      <td>8.760000</td>\n",
       "      <td>1.910000</td>\n",
       "      <td>92.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.390000</td>\n",
       "      <td>7.380000</td>\n",
       "      <td>1887.000000</td>\n",
       "      <td>19.790000</td>\n",
       "      <td>1463.000000</td>\n",
       "      <td>839.000000</td>\n",
       "      <td>15.890000</td>\n",
       "      <td>11.870000</td>\n",
       "      <td>575.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            hours       miles         feet         mph          vam  \\\n",
       "count  141.000000  141.000000   141.000000  141.000000   141.000000   \n",
       "mean     0.141702    0.932979   268.978723    7.444539   641.893617   \n",
       "std      0.173711    0.989832   295.060659    3.557336   211.923595   \n",
       "min      0.010000    0.080000    21.000000    2.120000   111.000000   \n",
       "25%      0.050000    0.330000   104.000000    4.830000   503.000000   \n",
       "50%      0.090000    0.600000   166.000000    6.190000   630.000000   \n",
       "75%      0.150000    1.190000   303.000000    9.800000   724.000000   \n",
       "max      1.390000    7.380000  1887.000000   19.790000  1463.000000   \n",
       "\n",
       "             fpmi         pct         kms      meters  \n",
       "count  141.000000  141.000000  141.000000  141.000000  \n",
       "mean   353.503546    6.694894    1.501064   81.978723  \n",
       "std    186.816320    3.537974    1.592267   89.957408  \n",
       "min     18.000000    0.350000    0.130000    6.000000  \n",
       "25%    219.000000    4.140000    0.530000   32.000000  \n",
       "50%    333.000000    6.300000    0.970000   51.000000  \n",
       "75%    462.000000    8.760000    1.910000   92.000000  \n",
       "max    839.000000   15.890000   11.870000  575.000000  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "segments.describe() # Summary statistics for the segments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 5/22/2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>Canada</td>\n",
       "      <td>2.19</td>\n",
       "      <td>36.68</td>\n",
       "      <td>1332</td>\n",
       "      <td>16.75</td>\n",
       "      <td>185.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.69</td>\n",
       "      <td>59.02</td>\n",
       "      <td>406.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Wed, 9/13/2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>Healdburg / Jimtown</td>\n",
       "      <td>2.13</td>\n",
       "      <td>34.45</td>\n",
       "      <td>912</td>\n",
       "      <td>16.17</td>\n",
       "      <td>131.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>55.43</td>\n",
       "      <td>278.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 8/25/2024</td>\n",
       "      <td>2024</td>\n",
       "      <td>Petaluma–Santa Rosa + Napa</td>\n",
       "      <td>5.22</td>\n",
       "      <td>84.26</td>\n",
       "      <td>2966</td>\n",
       "      <td>16.14</td>\n",
       "      <td>173.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.67</td>\n",
       "      <td>135.57</td>\n",
       "      <td>904.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 1/25/2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>Woodside</td>\n",
       "      <td>1.56</td>\n",
       "      <td>25.08</td>\n",
       "      <td>1243</td>\n",
       "      <td>16.08</td>\n",
       "      <td>243.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.94</td>\n",
       "      <td>40.35</td>\n",
       "      <td>379.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 4/11/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Woodside</td>\n",
       "      <td>1.54</td>\n",
       "      <td>24.73</td>\n",
       "      <td>1035</td>\n",
       "      <td>16.06</td>\n",
       "      <td>205.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.79</td>\n",
       "      <td>39.79</td>\n",
       "      <td>315.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mon, 5/27/2024</td>\n",
       "      <td>2024</td>\n",
       "      <td>Saratoga</td>\n",
       "      <td>4.83</td>\n",
       "      <td>77.25</td>\n",
       "      <td>1749</td>\n",
       "      <td>15.99</td>\n",
       "      <td>110.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.43</td>\n",
       "      <td>124.30</td>\n",
       "      <td>533.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 7/11/2021</td>\n",
       "      <td>2021</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>4.10</td>\n",
       "      <td>65.10</td>\n",
       "      <td>1086</td>\n",
       "      <td>15.88</td>\n",
       "      <td>81.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.32</td>\n",
       "      <td>104.75</td>\n",
       "      <td>331.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 1/18/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Woodside</td>\n",
       "      <td>1.64</td>\n",
       "      <td>26.02</td>\n",
       "      <td>1257</td>\n",
       "      <td>15.87</td>\n",
       "      <td>234.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>41.87</td>\n",
       "      <td>383.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 6/24/2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>Foothill Expway</td>\n",
       "      <td>1.59</td>\n",
       "      <td>25.11</td>\n",
       "      <td>623</td>\n",
       "      <td>15.79</td>\n",
       "      <td>119.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.47</td>\n",
       "      <td>40.40</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 1/26/2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>Canada Rd</td>\n",
       "      <td>2.10</td>\n",
       "      <td>33.12</td>\n",
       "      <td>1446</td>\n",
       "      <td>15.77</td>\n",
       "      <td>210.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.83</td>\n",
       "      <td>53.29</td>\n",
       "      <td>441.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 1/6/2012</td>\n",
       "      <td>2012</td>\n",
       "      <td>Omarama to Wanaka New Zealand</td>\n",
       "      <td>4.48</td>\n",
       "      <td>70.35</td>\n",
       "      <td>3262</td>\n",
       "      <td>15.70</td>\n",
       "      <td>222.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.88</td>\n",
       "      <td>113.19</td>\n",
       "      <td>994.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 4/12/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Palo Alto Cycling</td>\n",
       "      <td>2.03</td>\n",
       "      <td>31.76</td>\n",
       "      <td>1210</td>\n",
       "      <td>15.65</td>\n",
       "      <td>182.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.72</td>\n",
       "      <td>51.10</td>\n",
       "      <td>369.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 10/15/2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>Los Gatos</td>\n",
       "      <td>2.86</td>\n",
       "      <td>44.71</td>\n",
       "      <td>1437</td>\n",
       "      <td>15.63</td>\n",
       "      <td>153.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.61</td>\n",
       "      <td>71.94</td>\n",
       "      <td>438.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 8/5/2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>Bike Ride Northwest Day 1</td>\n",
       "      <td>3.58</td>\n",
       "      <td>55.77</td>\n",
       "      <td>1824</td>\n",
       "      <td>15.58</td>\n",
       "      <td>155.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.62</td>\n",
       "      <td>89.73</td>\n",
       "      <td>556.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 2/28/2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>Woodside Loop</td>\n",
       "      <td>1.73</td>\n",
       "      <td>26.93</td>\n",
       "      <td>843</td>\n",
       "      <td>15.57</td>\n",
       "      <td>149.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.59</td>\n",
       "      <td>43.33</td>\n",
       "      <td>257.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/26/2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>Los Gatos</td>\n",
       "      <td>3.28</td>\n",
       "      <td>50.78</td>\n",
       "      <td>1181</td>\n",
       "      <td>15.48</td>\n",
       "      <td>110.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.44</td>\n",
       "      <td>81.71</td>\n",
       "      <td>360.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mon, 1/19/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Canada Rd, etc.</td>\n",
       "      <td>2.95</td>\n",
       "      <td>45.64</td>\n",
       "      <td>1836</td>\n",
       "      <td>15.47</td>\n",
       "      <td>190.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.76</td>\n",
       "      <td>73.43</td>\n",
       "      <td>560.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 1/19/2014</td>\n",
       "      <td>2014</td>\n",
       "      <td>Palo Alto, CA</td>\n",
       "      <td>1.62</td>\n",
       "      <td>25.01</td>\n",
       "      <td>1201</td>\n",
       "      <td>15.44</td>\n",
       "      <td>226.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>40.24</td>\n",
       "      <td>366.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 12/6/2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>Canada Rd</td>\n",
       "      <td>2.25</td>\n",
       "      <td>34.67</td>\n",
       "      <td>1237</td>\n",
       "      <td>15.41</td>\n",
       "      <td>168.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.68</td>\n",
       "      <td>55.78</td>\n",
       "      <td>377.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tue, 6/18/2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>work etc (headwinds)</td>\n",
       "      <td>2.06</td>\n",
       "      <td>31.48</td>\n",
       "      <td>809</td>\n",
       "      <td>15.28</td>\n",
       "      <td>120.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>50.65</td>\n",
       "      <td>247.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             date  year                          title  hours  miles  feet  \\\n",
       "   Sun, 5/22/2016  2016                         Canada   2.19  36.68  1332   \n",
       "   Wed, 9/13/2017  2017            Healdburg / Jimtown   2.13  34.45   912   \n",
       "   Sun, 8/25/2024  2024     Petaluma–Santa Rosa + Napa   5.22  84.26  2966   \n",
       "   Sat, 1/25/2014  2014                       Woodside   1.56  25.08  1243   \n",
       "   Sat, 4/11/2015  2015                       Woodside   1.54  24.73  1035   \n",
       "   Mon, 5/27/2024  2024                       Saratoga   4.83  77.25  1749   \n",
       "   Sun, 7/11/2021  2021                       San Jose   4.10  65.10  1086   \n",
       "   Sun, 1/18/2015  2015                       Woodside   1.64  26.02  1257   \n",
       "   Fri, 6/24/2016  2016                Foothill Expway   1.59  25.11   623   \n",
       "   Sun, 1/26/2014  2014                      Canada Rd   2.10  33.12  1446   \n",
       "    Fri, 1/6/2012  2012  Omarama to Wanaka New Zealand   4.48  70.35  3262   \n",
       "   Sun, 4/12/2015  2015              Palo Alto Cycling   2.03  31.76  1210   \n",
       "  Sun, 10/15/2017  2017                      Los Gatos   2.86  44.71  1437   \n",
       "    Sun, 8/5/2018  2018      Bike Ride Northwest Day 1   3.58  55.77  1824   \n",
       "   Sun, 2/28/2016  2016                  Woodside Loop   1.73  26.93   843   \n",
       "   Sun, 6/26/2016  2016                      Los Gatos   3.28  50.78  1181   \n",
       "   Mon, 1/19/2015  2015                Canada Rd, etc.   2.95  45.64  1836   \n",
       "   Sun, 1/19/2014  2014                  Palo Alto, CA   1.62  25.01  1201   \n",
       "   Sun, 12/6/2015  2015                      Canada Rd   2.25  34.67  1237   \n",
       "   Tue, 6/18/2013  2013           work etc (headwinds)   2.06  31.48   809   \n",
       "\n",
       "    mph    vam  fpmi   pct     kms  meters  \n",
       "  16.75  185.0  36.0  0.69   59.02   406.0  \n",
       "  16.17  131.0  26.0  0.50   55.43   278.0  \n",
       "  16.14  173.0  35.0  0.67  135.57   904.0  \n",
       "  16.08  243.0  50.0  0.94   40.35   379.0  \n",
       "  16.06  205.0  42.0  0.79   39.79   315.0  \n",
       "  15.99  110.0  23.0  0.43  124.30   533.0  \n",
       "  15.88   81.0  17.0  0.32  104.75   331.0  \n",
       "  15.87  234.0  48.0  0.91   41.87   383.0  \n",
       "  15.79  119.0  25.0  0.47   40.40   190.0  \n",
       "  15.77  210.0  44.0  0.83   53.29   441.0  \n",
       "  15.70  222.0  46.0  0.88  113.19   994.0  \n",
       "  15.65  182.0  38.0  0.72   51.10   369.0  \n",
       "  15.63  153.0  32.0  0.61   71.94   438.0  \n",
       "  15.58  155.0  33.0  0.62   89.73   556.0  \n",
       "  15.57  149.0  31.0  0.59   43.33   257.0  \n",
       "  15.48  110.0  23.0  0.44   81.71   360.0  \n",
       "  15.47  190.0  40.0  0.76   73.43   560.0  \n",
       "  15.44  226.0  48.0  0.91   40.24   366.0  \n",
       "  15.41  168.0  36.0  0.68   55.78   377.0  \n",
       "  15.28  120.0  26.0  0.49   50.65   247.0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(rides, 'mph') # Fastest rides (of more than 20 miles, that I sampled into database)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>PCH Pescadero to Bean Hollow</td>\n",
       "      <td>0.14</td>\n",
       "      <td>2.77</td>\n",
       "      <td>51</td>\n",
       "      <td>19.79</td>\n",
       "      <td>111.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.35</td>\n",
       "      <td>4.46</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Highway 1  Cascanoa to Cascade</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1.61</td>\n",
       "      <td>89</td>\n",
       "      <td>17.89</td>\n",
       "      <td>301.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>1.05</td>\n",
       "      <td>2.59</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Vickrey Fruitvale</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.99</td>\n",
       "      <td>68</td>\n",
       "      <td>16.50</td>\n",
       "      <td>345.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.59</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Highway 9 Mantalvo</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.45</td>\n",
       "      <td>35</td>\n",
       "      <td>15.00</td>\n",
       "      <td>356.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>1.47</td>\n",
       "      <td>0.72</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Highway 9 Mantalvo</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.45</td>\n",
       "      <td>35</td>\n",
       "      <td>15.00</td>\n",
       "      <td>356.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>1.47</td>\n",
       "      <td>0.72</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>The Boneyard</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.48</td>\n",
       "      <td>135</td>\n",
       "      <td>14.80</td>\n",
       "      <td>411.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>1.73</td>\n",
       "      <td>2.38</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Vickrey Fruitvale</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.99</td>\n",
       "      <td>68</td>\n",
       "      <td>14.14</td>\n",
       "      <td>296.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.59</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sand Hill Alpine to 280</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1.67</td>\n",
       "      <td>180</td>\n",
       "      <td>13.92</td>\n",
       "      <td>457.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.04</td>\n",
       "      <td>2.69</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Canada to College</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>119</td>\n",
       "      <td>13.70</td>\n",
       "      <td>363.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1.65</td>\n",
       "      <td>2.20</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Foothill Homestead</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1.22</td>\n",
       "      <td>126</td>\n",
       "      <td>13.56</td>\n",
       "      <td>427.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1.96</td>\n",
       "      <td>1.96</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>The Boneyard</td>\n",
       "      <td>0.11</td>\n",
       "      <td>1.48</td>\n",
       "      <td>135</td>\n",
       "      <td>13.45</td>\n",
       "      <td>374.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>1.73</td>\n",
       "      <td>2.38</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kaboom Portola Rd</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.67</td>\n",
       "      <td>102</td>\n",
       "      <td>13.40</td>\n",
       "      <td>622.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>2.88</td>\n",
       "      <td>1.08</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Woodside Climb</td>\n",
       "      <td>0.13</td>\n",
       "      <td>1.71</td>\n",
       "      <td>295</td>\n",
       "      <td>13.15</td>\n",
       "      <td>692.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>3.27</td>\n",
       "      <td>2.75</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sand Hill Alpine to 280</td>\n",
       "      <td>0.13</td>\n",
       "      <td>1.67</td>\n",
       "      <td>180</td>\n",
       "      <td>12.85</td>\n",
       "      <td>422.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.04</td>\n",
       "      <td>2.69</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alpine Westridge</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.76</td>\n",
       "      <td>99</td>\n",
       "      <td>12.67</td>\n",
       "      <td>503.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>2.47</td>\n",
       "      <td>1.22</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alpine Westridge</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.76</td>\n",
       "      <td>99</td>\n",
       "      <td>12.67</td>\n",
       "      <td>503.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>2.47</td>\n",
       "      <td>1.22</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Stanford Ave</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.63</td>\n",
       "      <td>85</td>\n",
       "      <td>12.60</td>\n",
       "      <td>518.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>2.56</td>\n",
       "      <td>1.01</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Canada to College</td>\n",
       "      <td>0.11</td>\n",
       "      <td>1.37</td>\n",
       "      <td>119</td>\n",
       "      <td>12.45</td>\n",
       "      <td>330.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1.65</td>\n",
       "      <td>2.20</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sand Hill 280 to horse</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.49</td>\n",
       "      <td>95</td>\n",
       "      <td>12.25</td>\n",
       "      <td>724.0</td>\n",
       "      <td>194.0</td>\n",
       "      <td>3.67</td>\n",
       "      <td>0.79</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Stevens Country Park</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.22</td>\n",
       "      <td>112</td>\n",
       "      <td>12.20</td>\n",
       "      <td>341.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>1.74</td>\n",
       "      <td>1.96</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           title  hours  miles  feet    mph    vam   fpmi  \\\n",
       "    PCH Pescadero to Bean Hollow   0.14   2.77    51  19.79  111.0   18.0   \n",
       "  Highway 1  Cascanoa to Cascade   0.09   1.61    89  17.89  301.0   55.0   \n",
       "               Vickrey Fruitvale   0.06   0.99    68  16.50  345.0   69.0   \n",
       "              Highway 9 Mantalvo   0.03   0.45    35  15.00  356.0   78.0   \n",
       "              Highway 9 Mantalvo   0.03   0.45    35  15.00  356.0   78.0   \n",
       "                    The Boneyard   0.10   1.48   135  14.80  411.0   91.0   \n",
       "               Vickrey Fruitvale   0.07   0.99    68  14.14  296.0   69.0   \n",
       "         Sand Hill Alpine to 280   0.12   1.67   180  13.92  457.0  108.0   \n",
       "               Canada to College   0.10   1.37   119  13.70  363.0   87.0   \n",
       "              Foothill Homestead   0.09   1.22   126  13.56  427.0  103.0   \n",
       "                    The Boneyard   0.11   1.48   135  13.45  374.0   91.0   \n",
       "               Kaboom Portola Rd   0.05   0.67   102  13.40  622.0  152.0   \n",
       "                  Woodside Climb   0.13   1.71   295  13.15  692.0  173.0   \n",
       "         Sand Hill Alpine to 280   0.13   1.67   180  12.85  422.0  108.0   \n",
       "                Alpine Westridge   0.06   0.76    99  12.67  503.0  130.0   \n",
       "                Alpine Westridge   0.06   0.76    99  12.67  503.0  130.0   \n",
       "                    Stanford Ave   0.05   0.63    85  12.60  518.0  135.0   \n",
       "               Canada to College   0.11   1.37   119  12.45  330.0   87.0   \n",
       "          Sand Hill 280 to horse   0.04   0.49    95  12.25  724.0  194.0   \n",
       "            Stevens Country Park   0.10   1.22   112  12.20  341.0   92.0   \n",
       "\n",
       "   pct   kms  meters  \n",
       "  0.35  4.46    16.0  \n",
       "  1.05  2.59    27.0  \n",
       "  1.30  1.59    21.0  \n",
       "  1.47  0.72    11.0  \n",
       "  1.47  0.72    11.0  \n",
       "  1.73  2.38    41.0  \n",
       "  1.30  1.59    21.0  \n",
       "  2.04  2.69    55.0  \n",
       "  1.65  2.20    36.0  \n",
       "  1.96  1.96    38.0  \n",
       "  1.73  2.38    41.0  \n",
       "  2.88  1.08    31.0  \n",
       "  3.27  2.75    90.0  \n",
       "  2.04  2.69    55.0  \n",
       "  2.47  1.22    30.0  \n",
       "  2.47  1.22    30.0  \n",
       "  2.56  1.01    26.0  \n",
       "  1.65  2.20    36.0  \n",
       "  3.67  0.79    29.0  \n",
       "  1.74  1.96    34.0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments, 'mph') # Fastest segments (there are no descent segments in the database)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>West Alpine full</td>\n",
       "      <td>1.39</td>\n",
       "      <td>7.38</td>\n",
       "      <td>1887</td>\n",
       "      <td>5.31</td>\n",
       "      <td>414.0</td>\n",
       "      <td>256.0</td>\n",
       "      <td>4.84</td>\n",
       "      <td>11.87</td>\n",
       "      <td>575.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kings Greer to Skyline</td>\n",
       "      <td>0.78</td>\n",
       "      <td>3.92</td>\n",
       "      <td>1536</td>\n",
       "      <td>5.03</td>\n",
       "      <td>600.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>7.42</td>\n",
       "      <td>6.31</td>\n",
       "      <td>468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kings Greer to Skyline</td>\n",
       "      <td>0.81</td>\n",
       "      <td>3.92</td>\n",
       "      <td>1536</td>\n",
       "      <td>4.84</td>\n",
       "      <td>578.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>7.42</td>\n",
       "      <td>6.31</td>\n",
       "      <td>468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Old La Honda (Bridge to Stop)</td>\n",
       "      <td>0.48</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1255</td>\n",
       "      <td>6.94</td>\n",
       "      <td>797.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>7.14</td>\n",
       "      <td>5.36</td>\n",
       "      <td>383.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Old La Honda (Bridge to Stop)</td>\n",
       "      <td>0.51</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1255</td>\n",
       "      <td>6.53</td>\n",
       "      <td>750.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>7.14</td>\n",
       "      <td>5.36</td>\n",
       "      <td>383.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alma Mountain Charlie</td>\n",
       "      <td>0.53</td>\n",
       "      <td>3.12</td>\n",
       "      <td>875</td>\n",
       "      <td>5.89</td>\n",
       "      <td>503.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>5.31</td>\n",
       "      <td>5.02</td>\n",
       "      <td>267.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kings half way</td>\n",
       "      <td>0.46</td>\n",
       "      <td>2.89</td>\n",
       "      <td>820</td>\n",
       "      <td>6.28</td>\n",
       "      <td>543.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>5.37</td>\n",
       "      <td>4.65</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Kings half way</td>\n",
       "      <td>0.50</td>\n",
       "      <td>2.89</td>\n",
       "      <td>820</td>\n",
       "      <td>5.78</td>\n",
       "      <td>500.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>5.37</td>\n",
       "      <td>4.65</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alpine Portola to top Joaquin</td>\n",
       "      <td>0.57</td>\n",
       "      <td>3.52</td>\n",
       "      <td>801</td>\n",
       "      <td>6.18</td>\n",
       "      <td>428.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>4.31</td>\n",
       "      <td>5.66</td>\n",
       "      <td>244.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alpine Portola to top Joaquin</td>\n",
       "      <td>0.58</td>\n",
       "      <td>3.52</td>\n",
       "      <td>801</td>\n",
       "      <td>6.07</td>\n",
       "      <td>421.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>4.31</td>\n",
       "      <td>5.66</td>\n",
       "      <td>244.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tunitas steep</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.20</td>\n",
       "      <td>599</td>\n",
       "      <td>4.44</td>\n",
       "      <td>676.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>9.45</td>\n",
       "      <td>1.93</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tunitas steep</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.20</td>\n",
       "      <td>599</td>\n",
       "      <td>4.80</td>\n",
       "      <td>730.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>9.45</td>\n",
       "      <td>1.93</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Haskins</td>\n",
       "      <td>0.30</td>\n",
       "      <td>1.51</td>\n",
       "      <td>566</td>\n",
       "      <td>5.03</td>\n",
       "      <td>575.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>7.10</td>\n",
       "      <td>2.43</td>\n",
       "      <td>173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Haskins</td>\n",
       "      <td>0.31</td>\n",
       "      <td>1.51</td>\n",
       "      <td>566</td>\n",
       "      <td>4.87</td>\n",
       "      <td>557.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>7.10</td>\n",
       "      <td>2.43</td>\n",
       "      <td>173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Coe Second Switchback to flat</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.00</td>\n",
       "      <td>483</td>\n",
       "      <td>4.55</td>\n",
       "      <td>669.0</td>\n",
       "      <td>483.0</td>\n",
       "      <td>9.15</td>\n",
       "      <td>1.61</td>\n",
       "      <td>147.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Lower Redwood Gulch</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.03</td>\n",
       "      <td>474</td>\n",
       "      <td>4.68</td>\n",
       "      <td>657.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>8.72</td>\n",
       "      <td>1.66</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alpine Willowbrook to Joaquin</td>\n",
       "      <td>0.29</td>\n",
       "      <td>2.27</td>\n",
       "      <td>461</td>\n",
       "      <td>7.83</td>\n",
       "      <td>485.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>3.65</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Alpine Willowbrook to Joaquin</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2.27</td>\n",
       "      <td>461</td>\n",
       "      <td>8.11</td>\n",
       "      <td>502.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>3.65</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Lobitas Creek</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.96</td>\n",
       "      <td>430</td>\n",
       "      <td>4.80</td>\n",
       "      <td>655.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>8.48</td>\n",
       "      <td>1.54</td>\n",
       "      <td>131.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tunitas lower climb</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.30</td>\n",
       "      <td>421</td>\n",
       "      <td>5.91</td>\n",
       "      <td>583.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>6.13</td>\n",
       "      <td>2.09</td>\n",
       "      <td>128.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          title  hours  miles  feet   mph    vam   fpmi   pct  \\\n",
       "               West Alpine full   1.39   7.38  1887  5.31  414.0  256.0  4.84   \n",
       "         Kings Greer to Skyline   0.78   3.92  1536  5.03  600.0  392.0  7.42   \n",
       "         Kings Greer to Skyline   0.81   3.92  1536  4.84  578.0  392.0  7.42   \n",
       "  Old La Honda (Bridge to Stop)   0.48   3.33  1255  6.94  797.0  377.0  7.14   \n",
       "  Old La Honda (Bridge to Stop)   0.51   3.33  1255  6.53  750.0  377.0  7.14   \n",
       "          Alma Mountain Charlie   0.53   3.12   875  5.89  503.0  280.0  5.31   \n",
       "                 Kings half way   0.46   2.89   820  6.28  543.0  284.0  5.37   \n",
       "                 Kings half way   0.50   2.89   820  5.78  500.0  284.0  5.37   \n",
       "  Alpine Portola to top Joaquin   0.57   3.52   801  6.18  428.0  228.0  4.31   \n",
       "  Alpine Portola to top Joaquin   0.58   3.52   801  6.07  421.0  228.0  4.31   \n",
       "                  Tunitas steep   0.27   1.20   599  4.44  676.0  499.0  9.45   \n",
       "                  Tunitas steep   0.25   1.20   599  4.80  730.0  499.0  9.45   \n",
       "                        Haskins   0.30   1.51   566  5.03  575.0  375.0  7.10   \n",
       "                        Haskins   0.31   1.51   566  4.87  557.0  375.0  7.10   \n",
       "  Coe Second Switchback to flat   0.22   1.00   483  4.55  669.0  483.0  9.15   \n",
       "            Lower Redwood Gulch   0.22   1.03   474  4.68  657.0  460.0  8.72   \n",
       "  Alpine Willowbrook to Joaquin   0.29   2.27   461  7.83  485.0  203.0  3.85   \n",
       "  Alpine Willowbrook to Joaquin   0.28   2.27   461  8.11  502.0  203.0  3.85   \n",
       "                  Lobitas Creek   0.20   0.96   430  4.80  655.0  448.0  8.48   \n",
       "            Tunitas lower climb   0.22   1.30   421  5.91  583.0  324.0  6.13   \n",
       "\n",
       "    kms  meters  \n",
       "  11.87   575.0  \n",
       "   6.31   468.0  \n",
       "   6.31   468.0  \n",
       "   5.36   383.0  \n",
       "   5.36   383.0  \n",
       "   5.02   267.0  \n",
       "   4.65   250.0  \n",
       "   4.65   250.0  \n",
       "   5.66   244.0  \n",
       "   5.66   244.0  \n",
       "   1.93   183.0  \n",
       "   1.93   183.0  \n",
       "   2.43   173.0  \n",
       "   2.43   173.0  \n",
       "   1.61   147.0  \n",
       "   1.66   144.0  \n",
       "   3.65   141.0  \n",
       "   3.65   141.0  \n",
       "   1.54   131.0  \n",
       "   2.09   128.0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments, 'feet') # Biggest climbing segments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpmi</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>meters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Redwood Gulch hits</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.18</td>\n",
       "      <td>151</td>\n",
       "      <td>3.00</td>\n",
       "      <td>767.0</td>\n",
       "      <td>839.0</td>\n",
       "      <td>15.89</td>\n",
       "      <td>0.29</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Valparaiso steep</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.18</td>\n",
       "      <td>145</td>\n",
       "      <td>4.50</td>\n",
       "      <td>1105.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>15.26</td>\n",
       "      <td>0.29</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Valparaiso steep</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.18</td>\n",
       "      <td>145</td>\n",
       "      <td>3.60</td>\n",
       "      <td>884.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>15.26</td>\n",
       "      <td>0.29</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Limantour steepest</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.20</td>\n",
       "      <td>159</td>\n",
       "      <td>2.22</td>\n",
       "      <td>538.0</td>\n",
       "      <td>795.0</td>\n",
       "      <td>15.06</td>\n",
       "      <td>0.32</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Joaquin</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.33</td>\n",
       "      <td>254</td>\n",
       "      <td>3.30</td>\n",
       "      <td>774.0</td>\n",
       "      <td>770.0</td>\n",
       "      <td>14.58</td>\n",
       "      <td>0.53</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Joaquin</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.33</td>\n",
       "      <td>254</td>\n",
       "      <td>3.67</td>\n",
       "      <td>860.0</td>\n",
       "      <td>770.0</td>\n",
       "      <td>14.58</td>\n",
       "      <td>0.53</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Entrance Way Hill Repeats</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.10</td>\n",
       "      <td>76</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1158.0</td>\n",
       "      <td>760.0</td>\n",
       "      <td>14.39</td>\n",
       "      <td>0.16</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Stirrup Wall</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.17</td>\n",
       "      <td>125</td>\n",
       "      <td>2.83</td>\n",
       "      <td>635.0</td>\n",
       "      <td>735.0</td>\n",
       "      <td>13.93</td>\n",
       "      <td>0.27</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Stirrup Wall</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.17</td>\n",
       "      <td>125</td>\n",
       "      <td>2.12</td>\n",
       "      <td>476.0</td>\n",
       "      <td>735.0</td>\n",
       "      <td>13.93</td>\n",
       "      <td>0.27</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Westridge 3min</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.37</td>\n",
       "      <td>240</td>\n",
       "      <td>4.62</td>\n",
       "      <td>914.0</td>\n",
       "      <td>649.0</td>\n",
       "      <td>12.29</td>\n",
       "      <td>0.60</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Westridge 3min</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.37</td>\n",
       "      <td>240</td>\n",
       "      <td>4.11</td>\n",
       "      <td>813.0</td>\n",
       "      <td>649.0</td>\n",
       "      <td>12.29</td>\n",
       "      <td>0.60</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Limantour Spit</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.47</td>\n",
       "      <td>303</td>\n",
       "      <td>5.22</td>\n",
       "      <td>1026.0</td>\n",
       "      <td>645.0</td>\n",
       "      <td>12.21</td>\n",
       "      <td>0.76</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Klamath Dr.</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.12</td>\n",
       "      <td>77</td>\n",
       "      <td>6.00</td>\n",
       "      <td>1173.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>12.15</td>\n",
       "      <td>0.19</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>green valley kicker</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.29</td>\n",
       "      <td>178</td>\n",
       "      <td>3.62</td>\n",
       "      <td>678.0</td>\n",
       "      <td>614.0</td>\n",
       "      <td>11.62</td>\n",
       "      <td>0.47</td>\n",
       "      <td>54.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Redwood Gulch wall</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.43</td>\n",
       "      <td>258</td>\n",
       "      <td>3.91</td>\n",
       "      <td>715.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>11.36</td>\n",
       "      <td>0.69</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Paloma Climb</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.14</td>\n",
       "      <td>82</td>\n",
       "      <td>7.00</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>586.0</td>\n",
       "      <td>11.09</td>\n",
       "      <td>0.23</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Try not to fall back</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.71</td>\n",
       "      <td>410</td>\n",
       "      <td>3.38</td>\n",
       "      <td>595.0</td>\n",
       "      <td>577.0</td>\n",
       "      <td>10.94</td>\n",
       "      <td>1.14</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Westridge</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.68</td>\n",
       "      <td>385</td>\n",
       "      <td>4.86</td>\n",
       "      <td>838.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>10.72</td>\n",
       "      <td>1.09</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Westridge</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.68</td>\n",
       "      <td>385</td>\n",
       "      <td>4.25</td>\n",
       "      <td>733.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>10.72</td>\n",
       "      <td>1.09</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Stair Step</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.32</td>\n",
       "      <td>175</td>\n",
       "      <td>3.56</td>\n",
       "      <td>593.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>10.36</td>\n",
       "      <td>0.51</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      title  hours  miles  feet   mph     vam   fpmi    pct  \\\n",
       "         Redwood Gulch hits   0.06   0.18   151  3.00   767.0  839.0  15.89   \n",
       "           Valparaiso steep   0.04   0.18   145  4.50  1105.0  806.0  15.26   \n",
       "           Valparaiso steep   0.05   0.18   145  3.60   884.0  806.0  15.26   \n",
       "         Limantour steepest   0.09   0.20   159  2.22   538.0  795.0  15.06   \n",
       "                    Joaquin   0.10   0.33   254  3.30   774.0  770.0  14.58   \n",
       "                    Joaquin   0.09   0.33   254  3.67   860.0  770.0  14.58   \n",
       "  Entrance Way Hill Repeats   0.02   0.10    76  5.00  1158.0  760.0  14.39   \n",
       "               Stirrup Wall   0.06   0.17   125  2.83   635.0  735.0  13.93   \n",
       "               Stirrup Wall   0.08   0.17   125  2.12   476.0  735.0  13.93   \n",
       "             Westridge 3min   0.08   0.37   240  4.62   914.0  649.0  12.29   \n",
       "             Westridge 3min   0.09   0.37   240  4.11   813.0  649.0  12.29   \n",
       "             Limantour Spit   0.09   0.47   303  5.22  1026.0  645.0  12.21   \n",
       "                Klamath Dr.   0.02   0.12    77  6.00  1173.0  642.0  12.15   \n",
       "        green valley kicker   0.08   0.29   178  3.62   678.0  614.0  11.62   \n",
       "         Redwood Gulch wall   0.11   0.43   258  3.91   715.0  600.0  11.36   \n",
       "               Paloma Climb   0.02   0.14    82  7.00  1250.0  586.0  11.09   \n",
       "       Try not to fall back   0.21   0.71   410  3.38   595.0  577.0  10.94   \n",
       "                  Westridge   0.14   0.68   385  4.86   838.0  566.0  10.72   \n",
       "                  Westridge   0.16   0.68   385  4.25   733.0  566.0  10.72   \n",
       "                 Stair Step   0.09   0.32   175  3.56   593.0  547.0  10.36   \n",
       "\n",
       "   kms  meters  \n",
       "  0.29    46.0  \n",
       "  0.29    44.0  \n",
       "  0.29    44.0  \n",
       "  0.32    48.0  \n",
       "  0.53    77.0  \n",
       "  0.53    77.0  \n",
       "  0.16    23.0  \n",
       "  0.27    38.0  \n",
       "  0.27    38.0  \n",
       "  0.60    73.0  \n",
       "  0.60    73.0  \n",
       "  0.76    92.0  \n",
       "  0.19    23.0  \n",
       "  0.47    54.0  \n",
       "  0.69    79.0  \n",
       "  0.23    25.0  \n",
       "  1.14   125.0  \n",
       "  1.09   117.0  \n",
       "  1.09   117.0  \n",
       "  0.51    53.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments, 'pct') # Steepest climbs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
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       "      <th></th>\n",
       "      <td>Fri, 1/9/2012</td>\n",
       "      <td>2012</td>\n",
       "      <td>Otago Rail Trail Century</td>\n",
       "      <td>7.87</td>\n",
       "      <td>102.41</td>\n",
       "      <td>2286</td>\n",
       "      <td>13.01</td>\n",
       "      <td>89.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.42</td>\n",
       "      <td>164.78</td>\n",
       "      <td>697.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/7/2022</td>\n",
       "      <td>2022</td>\n",
       "      <td>Wine Country Century</td>\n",
       "      <td>6.65</td>\n",
       "      <td>100.26</td>\n",
       "      <td>5253</td>\n",
       "      <td>15.08</td>\n",
       "      <td>241.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.99</td>\n",
       "      <td>161.32</td>\n",
       "      <td>1601.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Thu, 6/14/2012</td>\n",
       "      <td>2012</td>\n",
       "      <td>Coyote Creek Century with Juliet</td>\n",
       "      <td>8.14</td>\n",
       "      <td>100.07</td>\n",
       "      <td>1513</td>\n",
       "      <td>12.29</td>\n",
       "      <td>57.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.29</td>\n",
       "      <td>161.01</td>\n",
       "      <td>461.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/13/2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>Morgan Hill iCare Classic</td>\n",
       "      <td>7.46</td>\n",
       "      <td>100.05</td>\n",
       "      <td>4596</td>\n",
       "      <td>13.41</td>\n",
       "      <td>188.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.87</td>\n",
       "      <td>160.98</td>\n",
       "      <td>1401.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 3/9/2024</td>\n",
       "      <td>2024</td>\n",
       "      <td>Millbrae / San Bruno / Sawyer Camp Trail / Bay...</td>\n",
       "      <td>8.12</td>\n",
       "      <td>98.52</td>\n",
       "      <td>4896</td>\n",
       "      <td>12.13</td>\n",
       "      <td>184.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.94</td>\n",
       "      <td>158.52</td>\n",
       "      <td>1492.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 9/20/2024</td>\n",
       "      <td>2024</td>\n",
       "      <td>Santa Rosa + Michael J Fox</td>\n",
       "      <td>6.28</td>\n",
       "      <td>93.33</td>\n",
       "      <td>3628</td>\n",
       "      <td>14.86</td>\n",
       "      <td>176.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>0.74</td>\n",
       "      <td>150.17</td>\n",
       "      <td>1106.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/12/2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>ICare Classic, Morgan Hill</td>\n",
       "      <td>6.80</td>\n",
       "      <td>91.29</td>\n",
       "      <td>4160</td>\n",
       "      <td>13.42</td>\n",
       "      <td>186.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.86</td>\n",
       "      <td>146.89</td>\n",
       "      <td>1268.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/6/2017</td>\n",
       "      <td>2017</td>\n",
       "      <td>Wine Country Century</td>\n",
       "      <td>7.26</td>\n",
       "      <td>89.49</td>\n",
       "      <td>5246</td>\n",
       "      <td>12.33</td>\n",
       "      <td>220.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>1.11</td>\n",
       "      <td>143.99</td>\n",
       "      <td>1599.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 8/10/2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>Bike Ride Northwest Day 6</td>\n",
       "      <td>6.24</td>\n",
       "      <td>84.70</td>\n",
       "      <td>4380</td>\n",
       "      <td>13.57</td>\n",
       "      <td>214.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>136.28</td>\n",
       "      <td>1335.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 2/28/2020</td>\n",
       "      <td>2020</td>\n",
       "      <td>Sawyer Camp Trail</td>\n",
       "      <td>6.41</td>\n",
       "      <td>84.43</td>\n",
       "      <td>3448</td>\n",
       "      <td>13.17</td>\n",
       "      <td>164.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0.77</td>\n",
       "      <td>135.85</td>\n",
       "      <td>1051.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 8/25/2024</td>\n",
       "      <td>2024</td>\n",
       "      <td>Petaluma–Santa Rosa + Napa</td>\n",
       "      <td>5.22</td>\n",
       "      <td>84.26</td>\n",
       "      <td>2966</td>\n",
       "      <td>16.14</td>\n",
       "      <td>173.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.67</td>\n",
       "      <td>135.57</td>\n",
       "      <td>904.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 6/1/2024</td>\n",
       "      <td>2024</td>\n",
       "      <td>OLH / Old Haul / Loma Mar / Pescadero / Tunita...</td>\n",
       "      <td>7.84</td>\n",
       "      <td>81.70</td>\n",
       "      <td>7314</td>\n",
       "      <td>10.42</td>\n",
       "      <td>284.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1.70</td>\n",
       "      <td>131.46</td>\n",
       "      <td>2229.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Wed, 6/7/2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>Los Altos</td>\n",
       "      <td>7.05</td>\n",
       "      <td>81.54</td>\n",
       "      <td>2110</td>\n",
       "      <td>11.57</td>\n",
       "      <td>91.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>131.20</td>\n",
       "      <td>643.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 8/30/2020</td>\n",
       "      <td>2020</td>\n",
       "      <td>Los Gatos</td>\n",
       "      <td>6.36</td>\n",
       "      <td>80.92</td>\n",
       "      <td>2100</td>\n",
       "      <td>12.72</td>\n",
       "      <td>101.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>130.20</td>\n",
       "      <td>640.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 9/17/2022</td>\n",
       "      <td>2022</td>\n",
       "      <td>San Gregorio / Tunitas</td>\n",
       "      <td>6.56</td>\n",
       "      <td>80.53</td>\n",
       "      <td>6015</td>\n",
       "      <td>12.28</td>\n",
       "      <td>279.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1.41</td>\n",
       "      <td>129.57</td>\n",
       "      <td>1833.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 10/1/2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>Half Moon Bay overnight campout</td>\n",
       "      <td>7.51</td>\n",
       "      <td>80.07</td>\n",
       "      <td>6039</td>\n",
       "      <td>10.66</td>\n",
       "      <td>245.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1.43</td>\n",
       "      <td>128.83</td>\n",
       "      <td>1841.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mon, 10/5/2020</td>\n",
       "      <td>2020</td>\n",
       "      <td>Half way around the bay on bay trail</td>\n",
       "      <td>6.44</td>\n",
       "      <td>80.05</td>\n",
       "      <td>541</td>\n",
       "      <td>12.43</td>\n",
       "      <td>26.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.13</td>\n",
       "      <td>128.80</td>\n",
       "      <td>165.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/21/2020</td>\n",
       "      <td>2020</td>\n",
       "      <td>Sawyer Camp Trail</td>\n",
       "      <td>6.59</td>\n",
       "      <td>79.78</td>\n",
       "      <td>1738</td>\n",
       "      <td>12.11</td>\n",
       "      <td>80.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.41</td>\n",
       "      <td>128.37</td>\n",
       "      <td>530.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Thu, 1/5/2012</td>\n",
       "      <td>2012</td>\n",
       "      <td>Tekapo Lake to Omarama New Zealand</td>\n",
       "      <td>5.46</td>\n",
       "      <td>79.42</td>\n",
       "      <td>2145</td>\n",
       "      <td>14.55</td>\n",
       "      <td>120.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.51</td>\n",
       "      <td>127.79</td>\n",
       "      <td>654.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tue, 8/7/2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>Bike Ride Northwest Day 3</td>\n",
       "      <td>6.18</td>\n",
       "      <td>78.96</td>\n",
       "      <td>5092</td>\n",
       "      <td>12.78</td>\n",
       "      <td>251.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>1.22</td>\n",
       "      <td>127.05</td>\n",
       "      <td>1552.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            date  year                                              title  \\\n",
       "   Fri, 1/9/2012  2012                           Otago Rail Trail Century   \n",
       "   Sat, 5/7/2022  2022                               Wine Country Century   \n",
       "  Thu, 6/14/2012  2012                   Coyote Creek Century with Juliet   \n",
       "  Sat, 5/13/2017  2017                          Morgan Hill iCare Classic   \n",
       "   Sat, 3/9/2024  2024  Millbrae / San Bruno / Sawyer Camp Trail / Bay...   \n",
       "  Fri, 9/20/2024  2024                         Santa Rosa + Michael J Fox   \n",
       "  Sat, 5/12/2018  2018                         ICare Classic, Morgan Hill   \n",
       "   Sat, 5/6/2017  2017                               Wine Country Century   \n",
       "  Fri, 8/10/2018  2018                          Bike Ride Northwest Day 6   \n",
       "  Fri, 2/28/2020  2020                                  Sawyer Camp Trail   \n",
       "  Sun, 8/25/2024  2024                         Petaluma–Santa Rosa + Napa   \n",
       "   Sat, 6/1/2024  2024  OLH / Old Haul / Loma Mar / Pescadero / Tunita...   \n",
       "   Wed, 6/7/2023  2023                                          Los Altos   \n",
       "  Sun, 8/30/2020  2020                                          Los Gatos   \n",
       "  Sat, 9/17/2022  2022                             San Gregorio / Tunitas   \n",
       "  Sat, 10/1/2016  2016                    Half Moon Bay overnight campout   \n",
       "  Mon, 10/5/2020  2020               Half way around the bay on bay trail   \n",
       "  Sun, 6/21/2020  2020                                  Sawyer Camp Trail   \n",
       "   Thu, 1/5/2012  2012                 Tekapo Lake to Omarama New Zealand   \n",
       "   Tue, 8/7/2018  2018                          Bike Ride Northwest Day 3   \n",
       "\n",
       "  hours   miles  feet    mph    vam  fpmi   pct     kms  meters  \n",
       "   7.87  102.41  2286  13.01   89.0  22.0  0.42  164.78   697.0  \n",
       "   6.65  100.26  5253  15.08  241.0  52.0  0.99  161.32  1601.0  \n",
       "   8.14  100.07  1513  12.29   57.0  15.0  0.29  161.01   461.0  \n",
       "   7.46  100.05  4596  13.41  188.0  46.0  0.87  160.98  1401.0  \n",
       "   8.12   98.52  4896  12.13  184.0  50.0  0.94  158.52  1492.0  \n",
       "   6.28   93.33  3628  14.86  176.0  39.0  0.74  150.17  1106.0  \n",
       "   6.80   91.29  4160  13.42  186.0  46.0  0.86  146.89  1268.0  \n",
       "   7.26   89.49  5246  12.33  220.0  59.0  1.11  143.99  1599.0  \n",
       "   6.24   84.70  4380  13.57  214.0  52.0  0.98  136.28  1335.0  \n",
       "   6.41   84.43  3448  13.17  164.0  41.0  0.77  135.85  1051.0  \n",
       "   5.22   84.26  2966  16.14  173.0  35.0  0.67  135.57   904.0  \n",
       "   7.84   81.70  7314  10.42  284.0  90.0  1.70  131.46  2229.0  \n",
       "   7.05   81.54  2110  11.57   91.0  26.0  0.49  131.20   643.0  \n",
       "   6.36   80.92  2100  12.72  101.0  26.0  0.49  130.20   640.0  \n",
       "   6.56   80.53  6015  12.28  279.0  75.0  1.41  129.57  1833.0  \n",
       "   7.51   80.07  6039  10.66  245.0  75.0  1.43  128.83  1841.0  \n",
       "   6.44   80.05   541  12.43   26.0   7.0  0.13  128.80   165.0  \n",
       "   6.59   79.78  1738  12.11   80.0  22.0  0.41  128.37   530.0  \n",
       "   5.46   79.42  2145  14.55  120.0  27.0  0.51  127.79   654.0  \n",
       "   6.18   78.96  5092  12.78  251.0  64.0  1.22  127.05  1552.0  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(rides, 'miles') # Longest rides"
   ]
  }
 ],
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